Creating a digital approach for promoting physical activity in pediatric pulmonary hypertension: A framework for future interventions.

Children with pulmonary hypertension (PH) often demonstrate limited exercise capacity. Data support exercise as an effective nonpharmacologic intervention among adults with PH. However, data on exercise training in children and adolescents are limited, and characteristics of the optimal exercise program in pediatric PH have not been identified. Exercise programs may have multiple targets, including muscle deficits which are associated with exercise limitations in both adult and pediatric PH. Wearable accelerometer sensors measure physical activity volume and intensity in the naturalistic setting and can facilitate near continuous data transfer and bidirectional communication between patients and the study team when paired with informatics tools during exercise interventions. To address the knowledge gaps in exercise training in pediatric PH, we designed a prospective, single arm, nonrandomized pilot study to determine feasibility and preliminary estimates of efficacy of a 16-week home exercise intervention, targeting lower extremity muscle mass and enriched by wearable mobile health technology. The exercIse Training in pulmONary hypertEnsion (iTONE) trial includes (1) semistructured exercise prescriptions tailored to the participant's baseline level of activity and access to resources; (2) interval goal setting fostering self-efficacy; (3) real time monitoring of activity via wearable devices; (4) a digital platform enabling communication and feedback between participant and study team; (5) multiple avenues to assess participant safety. This pilot intervention will provide information on the digital infrastructure needed to conduct home-based exercise interventions in PH and will generate important preliminary data on the effect of exercise interventions in youth with chronic cardiorespiratory conditions to power larger studies in the future.

Associations between Sleep and Physical Activity Behavior Clusters and Epigenetic Age Acceleration in Mexican Adolescents.

INTRODUCTION: Epigenetic aging, a marker of biological aging measured by DNA methylation, may be affected by behaviors, including sleep and physical activity. However, investigations of physical activity and sleep with epigenetic aging among pediatric populations are scant and have not accounted for correlated behaviors. METHODS: The study population included 472 Mexico City adolescents (52% female). Blood collection and 7-day wrist actigraphy (Actigraph GTX-BT) occurred during a follow-up visit when participants were 14.5 (2.09) years. Leukocyte DNA methylation was measured with the Infinium MethylationEPIC array after bisulfite conversion, and 9 epigenetic clocks were calculated. Sleep vs wake time was identified through a pruned dynamic programing algorithm, and physical activity was processed with Chandler cut-offs. Kmeans clustering was used to select actigraphy-assessed physical activity and sleep behavior clusters. Linear regression analyses were used to evaluate adjusted associations between the clusters and epigenetic aging. RESULTS: There were 3 unique clusters: "Short sleep/high sedentary behavior", "Adequate sleep duration and late timing/low moderate or vigorous physical activity (MVPA)", and "Adequate sleep duration/high MVPA". Compared to the "Adequate duration/high MVPA", adolescents with "Adequate duration and late sleep timing/low MVPA" had more accelerated aging for the GrimAge clock (ß = 0.63;95% CI 0.07, 1.19). In pubertal-stratified analyses, more mature adolescents in the "Adequate duration and late sleep timing/low MVPA group" had accelerated epigenetic aging. In contrast, females in the "Short sleep/high sedentary" group had decelerated epigenetic aging for the Wu pediatric clock. CONCLUSIONS: Associations between behavior clusters and epigenetic aging varied by pubertal status and sex. Contrary results in the Wu clock suggest the need for future research on pediatric-specific clocks.

Sleep Duration and Blood Pressure in Youth Referred for Elevated Blood Pressure Evaluation.

OBJECTIVES: Sleep promotion is not specifically recommended as a target for hypertension management. We examined associations of sleep duration and timing with blood pressure parameters in patients referred to pediatric nephrology clinic for elevated blood pressure evaluation. METHODS: This is a retrospective study of initial ambulatory blood pressure monitoring data and self-report sleep data collected from patients referred to nephrology clinic for the evaluation of elevated blood pressure. Linear and logistic regression modeling determined associations between sleep exposures (duration and timing) and continuous and dichotomous blood pressure outcomes, respectively, adjusted for age, sex, body mass index, and weekday versus weekend status. RESULTS: The study sample included 539 patients with mean age 14.6 years and 56% meeting hypertension criteria. Sleep duration averaged 9.1 hours per night. Average timing of sleep onset and offset were 11:06 pm and 8:18 am, respectively. Longer sleep duration was associated with better daytime blood pressure parameters (eg, every extra hour of sleep duration was associated with a reduced odds of wake hypertension [odds ratio, 0.88; 95% CI, 0.79-0.99]). Later sleep onset was associated with worse daytime blood pressure parameters (eg, each additional hour of later sleep onset was associated with higher wake systolic blood pressure index [mean wake blood pressure/95th percentile]) (ß = 0.07; 95% CI, 0.02-0.13). Associations were consistent across sex, age, body mass index, and weekday status. CONCLUSIONS: Longer sleep duration and earlier sleep onset were associated with lower blood pressure. This suggests that sleep optimization may be an important target for intervention in hypertension management.

Gamification to Promote Physical Activity in Youth and Mothers With Obesity.

PURPOSE: Physical inactivity and sugar-sweetened beverage (SSB) consumption are associated with obesity. Gamification and self-monitoring to promote physical activity in youth is unknown, but evidence of effectiveness is present in adults. This study examined the effects of a gamification intervention on increased steps per day among parent-adolescent dyads with obesity compared with digital self-monitoring and if self-monitored SSB intake differed between these arms. METHODS: Youth ages 10-16 years and their mothers (N = 39 pairs), both with obesity, were randomized to a self-monitoring (N = 18) or a self-monitoring plus gamification arm (N = 21) for 9 weeks. The step goal was set and incrementally increased each week and was measured with Fitbit devices. Mixed effects linear regression examined changes in steps and SSB consumption per day, per week by study arm. RESULTS: During run-in, mothers averaged 8317 and youth 7508 steps per day. Compared with self-monitoring alone, gamification did not increase daily steps in mothers or youth beyond baseline levels. On average, SSB intake decreased in mothers by approximately 0.5 servings per day; occurred in both arms and persisted throughout the intervention. CONCLUSION: Gamification did not promote physical activity levels in mother-youth dyads with obesity. SSB intake declined in mothers with obesity in both study arms.

Ethical considerations in using sensors to remotely assess pediatric health behaviors.

Sensors, including accelerometer-based and electronic adherence monitoring devices, have transformed health data collection. Sensors allow for unobtrusive, real-time sampling of health behaviors that relate to psychological health, including sleep, physical activity, and medication-taking. These technical strengths have captured scholarly attention, with far less discussion about the level of human touch involved in implementing sensors. Researchers face several subjective decision points when collecting health data via sensors, with these decisions posing ethical concerns for users and the public at large. Using examples from pediatric sleep, physical activity, and medication adherence research, we pose critical ethical questions, practical dilemmas, and guidance for implementing health-based sensors. We focus on youth given that they are often deemed the ideal population for digital health approaches but have unique technology-related vulnerabilities and preferences. Ethical considerations are organized according to Belmont principles of respect for persons (e.g., when sensor-based data are valued above the subjective lived experiences of youth and their families), beneficence (e.g., with sensor data management and sharing), and justice (e.g., with sensor access and acceptability among minoritized pediatric populations). Recommendations include the need to increase transparency about the extent of subjective decision making with sensor data management. Without greater attention to the human factors involved in sensor research, ethical risks could outweigh the scientific promise of sensors, thereby negating their potential role in improving child health and care. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Reference ranges for body composition indices by dual energy X-ray absorptiometry from the Bone Mineral Density in Childhood Study Cohort.

BACKGROUND: Body composition assessment aids evaluation of energy stores and the impact of diseases and interventions on child growth. Current United States pediatric reference ranges from the National Health and Nutrition Examination Survey (NHANES) include 20% of children with obesity, body mass index of ≥95th percentile. OBJECTIVES: This study aimed to develop dual energy X-ray absorptiometry (DXA) based reference ranges in a diverse cohort with low-obesity prevalence from the Bone Mineral Density in Childhood Study (BMDCS). METHODS: This is a secondary analysis of a longitudinal, prospective, observational cohort. Healthy children (height and BMI within 3rd to 97th percentiles, ages 5-19 y at enrollment), from 5 United States centers were measured annually for ≤7 visits. Whole body scans were acquired using Hologic scanners. A subsample underwent repeat measurements to determine precision. We generated reference ranges for appendicular and total lean soft tissue mass index (LSTM Index), fat mass index (FMI), and other body composition measures. Resulting curves were compared to NHANES and across subgroups. Sex and age-specific equations were developed to adjust body composition Z-scores for height Z score. RESULTS: We obtained 9846 scans of 2011 participants (51% female, 22% Black, 17% Hispanic, 48% White, 7% Asian/Pacific Islander, and 6% with obesity). Precision (percent coefficient of variation) ranged from 0.7% to 1.96%. Median and-2 standard deviation curves for BMDCS and NHANES were similar, but NHANES +2 standard deviation LSTM Index and FMI curves were distinctly greater than the respective BMDCS curves. Subgroup differences were more extreme for appendicular LSTM Index-Z (mean ± SD: Asian -0.52 ± 0.93 compared with Black 0.77 ± 0.87) than for FMI-Z (Hispanic 0.29 ± 0.98 compared with Black -0.14 ± 1.1) and were smaller for Z-scores adjusted for height Z-score. CONCLUSIONS: These reference ranges add to sparse normative data regarding body composition in children and adolescents and are based on a cohort with an obesity prevalence similar to current BMI charts. Awareness of subgroup differences aids in interpreting results.

The neighborhood environment and sleep health in adolescents.

OBJECTIVE: Neighborhood-level factors, including education, health and environment, and socioeconomic exposures, are important contextual determinants of child health. We explored whether these factors, measured via the Childhood Opportunity Index 2.0, were associated with sleep health in adolescents. METHODS: Actigraphy was used to assess sleep duration, timing, and efficiency among 110 adolescents in eighth (13.9 (0.4)) and ninth (14.9 (0.4)) grade. Home addresses were geocoded and linked to Childhood Opportunity Index 2.0 scores (including 3 subtype scores and the 29 individual factor Z-scores). Mixed-effects linear regression was used to determine associations between the Childhood Opportunity Index 2.0 scores and the sleep outcomes, adjusting for sex, race, parent education, household income, school grade and weeknight status. Interactions were also tested by school grade, weeknight status, sex, and race. RESULTS: No associations were observed between overall or subtype scores with sleep outcomes in adolescents. However, we detected associations between select individual Childhood Opportunity Index 2.0 Z-scores, spanning health & environment and education domains, and sleep outcomes. For example, greater fine particulate matter was associated with later timing of sleep onset and offset; ozone concentration was associated with earlier sleep onset and offset; greater exposure to extreme temperature was associated with later sleep onset and offset and increased odds of optimal sleep efficiency. CONCLUSIONS: Specific neighborhood factors indexed by the Childhood Opportunity Index 2.0 were associated with sleep health among adolescents. In particular, neighborhood air quality measures were associated with sleep timing and efficiency, warranting further investigation.

Associations of bedroom PM2.5, CO2, temperature, humidity, and noise with sleep: An observational actigraphy study.

OBJECTIVE: Climate change and urbanization increasingly cause extreme conditions hazardous to health. The bedroom environment plays a key role for high-quality sleep. Studies objectively assessing multiple descriptors of the bedroom environment as well as sleep are scarce. METHODS: Particulate matter with a particle size <2.5 µm (PM2.5), temperature, humidity, carbon dioxide (CO2), barometric pressure, and noise levels were continuously measured for 14 consecutive days in the bedroom of 62 participants (62.9% female, mean ± SD age: 47.7 ± 13.2 years) who wore a wrist actigraph and completed daily morning surveys and sleep logs. RESULTS: In a hierarchical mixed effect model that included all environmental variables and adjusted for elapsed sleep time and multiple demographic and behavioral variables, sleep efficiency calculated for consecutive 1-hour periods decreased in a dose-dependent manner with increasing levels of PM2.5, temperature, CO2, and noise. Sleep efficiency in the highest exposure quintiles was 3.2% (PM2.5, p < .05), 3.4% (temperature, p < .05), 4.0% (CO2, p < .01), and 4.7% (noise, p < .0001) lower compared to the lowest exposure quintiles (all p-values adjusted for multiple testing). Barometric pressure and humidity were not associated with sleep efficiency. Bedroom humidity was associated with subjectively assessed sleepiness and poor sleep quality (both p < .05), but otherwise environmental variables were not statistically significantly associated with actigraphically assessed total sleep time and wake after sleep onset or with subjectively assessed sleep onset latency, sleep quality, and sleepiness. Assessments of bedroom comfort suggest subjective habituation irrespective of exposure levels. CONCLUSIONS: These findings add to a growing body of evidence highlighting the importance of the bedroom environment-beyond the mattress-for high-quality sleep.

Feasibility and acceptability of mobile methods to assess home and neighborhood environments related to adolescent sleep.

OBJECTIVE: A growing evidence base suggests home and neighborhood environmental exposures may influence adolescent sleep, but few studies have assessed these relationships using methods that account for time-varying, location-specific exposures, or multiple neighborhood contexts. This study aimed to assess the feasibility and acceptability of using smartphone global positioning system (GPS) tracking and ecological momentary assessment (EMA) to assess time-varying home and neighborhood environmental exposures hypothesized to be associated with adolescent sleep. METHODS: Adolescents aged 15-17 years in Philadelphia completed 7 days of continuous smartphone GPS tracking, which was used to identify daily levels of exposure to geocoded neighborhood factors (eg, crime, green space). Four daily EMA surveys assessed home sleep environment (eg, noise, light), stress, health behaviors, and neighborhood perceptions. Feasibility and acceptability of GPS tracking and EMA were assessed, and distributions of daily environmental exposures were examined. RESULTS: Among 25 teens (mean age 16, 56% male), there was a high level of GPS location data captured (median daily follow-up: 24 hours). Seventy-eight percent of EMA surveys were completed overall. Most participants (96%) reported no privacy concerns related to GPS tracking and minimal burden from EMA surveys. Exposures differed between participants' home neighborhoods and locations visited outside the home neighborhood (eg, higher crime away from home). Sleep environment disruptions were present on 29% of nights (most common: uncomfortable temperature) and were reported by 52% of adolescents. CONCLUSIONS: Results demonstrate the feasibility and acceptability of mobile methods for assessing time-varying home and neighborhood exposures relevant to adolescent sleep for up to 1 week.

Promoting Sleep Duration in the Pediatric Setting Using a Mobile Health Platform: A Randomized Optimization Trial.

Objective: Determine the optimal combination of digital health intervention component settings that increase average sleep duration by ≥30 minutes per weeknight. Methods: Optimization trial using a 25 factorial design. The trial included 2 week run-in, 7 week intervention, and 2 week follow-up periods. Typically developing children aged 9-12y, with weeknight sleep duration <8.5 hours were enrolled (N=97). All received sleep monitoring and performance feedback. The five candidate intervention components (with their settings to which participants were randomized) were: 1) sleep goal (guideline-based or personalized); 2) screen time reduction messaging (inactive or active); 3) daily routine establishing messaging (inactive or active); 4) child-directed loss-framed financial incentive (inactive or active); and 5) caregiver-directed loss-framed financial incentive (inactive or active). The primary outcome was weeknight sleep duration (hours per night). The optimization criterion was: ≥30 minutes average increase in sleep duration on weeknights. Results: Average baseline sleep duration was 7.7 hours per night. The highest ranked combination included the core intervention plus the following intervention components: sleep goal (either setting was effective), caregiver-directed loss-framed incentive, messaging to reduce screen time, and messaging to establish daily routines. This combination increased weeknight sleep duration by an average of 39.6 (95% CI: 36.0, 43.1) minutes during the intervention period and by 33.2 (95% CI: 28.9, 37.4) minutes during the follow-up period. Conclusions: Optimal combinations of digital health intervention component settings were identified that effectively increased weeknight sleep duration. This could be a valuable remote patient monitoring approach to treat insufficient sleep in the pediatric setting.

Sufficient sleep duration in autistic children and the role of physical activity.

LAY ABSTRACT: Higher levels of physical activity may be associated with improved sleep in children, but this relationship is still being determined, especially in autistic children. In this study, we used existing data from the 2018 National Survey of Children's Health. Caregivers of children 6-17 years old, including caregivers of autistic children, completed a questionnaire that included questions about physical activity (days active in the past week) and sleep duration. We then determined if children were obtaining the recommended hours of sleep for their age (i.e. sufficient sleep). We found that higher physical activity levels were associated with sufficient sleep duration, but this finding was weaker in autistic children. In particular, this association was not observed in autistic children with more severe autism spectrum disorder, female autistic children, and autistic children 6-12 years old. In conclusion, physical activity is a promising approach to help children obtain sufficient sleep duration. However, more personalized approaches to improving sleep may be needed for certain groups of autistic children.

The relationship between autism spectrum and sleep-wake traits.

Autistic children and adults often have sleep disturbances, which may affect their and their family's quality of life. Yet, the relationship between sleep-wake patterns and autism spectrum traits is understudied. Identifying such relationships could lead to future research elucidating common mechanistic underpinnings. Thus, we aimed to determine whether sleep-wake patterns, specifically related to sleep, physical activity, and the daily sleep-wake rhythm (i.e., circadian rhythm), are associated with autism spectrum-related traits. Accelerometer-derived sleep-wake parameters were estimated in individuals with autistic spectrum traits and their family members (N = 267). We evaluated autism spectrum traits using the Social Responsiveness Scale (SRS) to assess the presence and severity of social impairment and the Behavior Rating Inventory of Executive Function (BRIEF) to assess executive function. The linear multivariate regression analysis (using SOLAR-Eclipse) showed that in adults, increased core autism spectrum traits and executive dysfunction were associated with disruption of several sleep-wake parameters, particularly related to the daily sleep-wake rhythm, and that executive dysfunction was associated with disrupted sleep quality and level of physical activity. We highlight the interplay between daytime function and disrupted sleep-wake patterns, specifically related to the daily sleep-wake rhythm, that could guide future research into common mechanisms. LAY SUMMARY: Autistic children and adults often report sleep disturbances. To dissect the relationship between a range of autism spectrum traits and sleep-wake patterns, we assessed social interaction and executive function in participants who also wore actimetry watches on their wrists to assess their sleep-wake patterns. We found that increased impairments in social and executive function occurred with increased sleep-wake disturbances, particularly those related to the circadian rhythm, suggesting that these perturbations/disruptions in the sleep-wake cycle could be connected to autism spectrum traits.

Body Mass Index and Height in the Friedreich Ataxia Clinical Outcome Measures Study.

BACKGROUND AND OBJECTIVES: Body mass index (BMI) and height are important indices of health. We tested the association between these outcomes and clinical characteristics in Friedreich ataxia (FRDA), a progressive neuromuscular disorder. METHODS: Participants (N = 961) were enrolled in a prospective natural history study (Friedreich Ataxia Clinical Outcome Measure Study). Age- and sex-specific BMI and height Z-scores were calculated using CDC 2000 references for participants younger than 18 years. For adults aged 18 years or older, height Z-scores were also calculated, and absolute BMI was reported. Univariate and multivariate linear regression analyses tested the associations between exposures, covariates, and BMI or height measured at the baseline visit. In children, the superimposition by translation and rotation analysis method was used to compare linear growth trajectories between FRDA and a healthy reference cohort, the Bone Mineral Density in Childhood Study (n = 1,535 used for analysis). RESULTS: Median age at the baseline was 20 years (IQR, 13-33 years); 49% (n = 475) were women. A substantial proportion of children (17%) were underweight (BMI-Z < fifth percentile), and female sex was associated with lower BMI-Z (ß = -0.34, p < 0.05). In adults, older age was associated with higher BMI (ß = 0.09, p < 0.05). Regarding height, in children, older age (ß -0.06, p < 0.05) and worse modified Friedreich Ataxia Rating Scale (mFARS) scores (ß = -1.05 for fourth quartile vs first quartile, p < 0.01) were associated with shorter stature. In girls, the magnitude of the pubertal growth spurt was less, and in boys, the pubertal growth spurt occurred later (p < 0.001 for both) than in a healthy reference cohort. In adults, in unadjusted analyses, both earlier age of FRDA symptom onset (=0.09, p < 0.05) and longer guanine-adenine-adenine repeat length (shorter of the 2 GAA repeats, ß = -0.12, p < 0.01) were associated with shorter stature. Both adults and children with higher mFARS scores and/or who were nonambulatory were less likely to have height and weight measurements recorded at clinical visits. DISCUSSION: FRDA affects both weight gain and linear growth. These insights will inform assessments of affected individuals in both research and clinical settings.

CYP11B1 variants influence skeletal maturation via alternative splicing.

We performed genome-wide association study meta-analysis to identify genetic determinants of skeletal age (SA) deviating in multiple growth disorders. The joint meta-analysis (N = 4557) in two multiethnic cohorts of school-aged children identified one locus, CYP11B1 (expression confined to the adrenal gland), robustly associated with SA (rs6471570-A; ß = 0.14; P = 6.2 × 10-12). rs6410 (a synonymous variant in the first exon of CYP11B1 in high LD with rs6471570), was prioritized for functional follow-up being second most significant and the one closest to the first intron-exon boundary. In 208 adrenal RNA-seq samples from GTEx, C-allele of rs6410 was associated with intron 3 retention (P = 8.11 × 10-40), exon 4 inclusion (P = 4.29 × 10-34), and decreased exon 3 and 5 splicing (P = 7.85 × 10-43), replicated using RT-PCR in 15 adrenal samples. As CYP11B1 encodes 11-ß-hydroxylase, involved in adrenal glucocorticoid and mineralocorticoid biosynthesis, our findings highlight the role of adrenal steroidogenesis in SA in healthy children, suggesting alternative splicing as a likely underlying mechanism.

Engineering a mobile platform to promote sleep in the pediatric primary care setting.

STUDY OBJECTIVES: Pediatricians lack tools to support families at home for the promotion of childhood sleep. We are using the Multiphase Optimization Strategy (MOST) framework to guide the development of a mobile health platform for childhood sleep promotion. The objective of this study is to demonstrate feasibility of a mobile health platform towards treating children with insufficient sleep. METHODS: Children aged 10-12 years were enrolled (Study #1: N = 30; Study #2: N = 43). Participants wore a sleep tracker to measure sleep duration. Data were retrieved by a mobile health platform, programmed to send introductory messages during run-in (2 weeks) and goal achievement messages during intervention (7 weeks) periods. In study #1, participants were randomized to control, gain-framed incentive or loss-framed incentive arms. In study #2, participants were randomized to control, loss-framed incentive, normative feedback or loss-framed incentive plus normative feedback arms. RESULTS: In study #1, 1514 nights of data were captured (69%) and sleep duration during the intervention was higher by an average of 21 (95% CI: -8, 51) and 34 (95% CI: 7, 61) minutes per night for the gain-framed and loss-framed arms, respectively, compared to controls. In study #2, 2,689 nights of data were captured (81%), with no major differences in average sleep duration between the control and the loss-framed or normative feedback arms. CONCLUSIONS: We have developed and deployed a mobile health platform that can capture sleep data and remotely communicate with families. Promising candidate intervention components will be further investigated under the optimization phase of the MOST framework. CLINICAL TRIALS: Both studies included in this manuscript were registered at clinicaltrials.gov:-Study #1: NCT03263338-Study #2: NCT03426644.

Neighborhood environments and sleep among children and adolescents: A systematic review.

Understanding salient environmental determinants of pediatric sleep is essential for informing interventions and public health initiatives. Emerging evidence suggests that the neighborhood environment can impact pediatric sleep, but this evidence has not yet been systematically reviewed. We conducted a systematic review of the scientific literature on associations between neighborhood environments and sleep in young children (0-5 y), school-aged children (6-12 y) and adolescents (13-18 y). We reviewed 85 articles published between 2003 and 2020. The most commonly examined neighborhood exposure was low socioeconomic status (40 studies), which was associated with sleep outcomes in 58% of studies (primarily shorter sleep duration, later sleep timing, or obstructive sleep apnea). Evidence was stronger for neighborhood safety/crime/violence (21 studies), with 86% of studies reporting associations with sleep outcomes (primarily self- or caregiver-reported sleep problems). Fewer studies examined associations of neighborhood physical environment exposures, including noise (15 studies), the built environment (seven studies), and air pollution (six studies). Limitations of the current body of evidence include 1) limited examination of neighborhood exposures other than socioeconomic status or safety, 2) use of primarily cross-sectional observational study designs, 3) lack of objective sleep outcome assessment, and 4) limits of current exposure assessment methods.

Associations of the residential built environment with adolescent sleep outcomes.

STUDY OBJECTIVES: Over 75% of US high school students obtain insufficient sleep, placing them at risk for adverse health outcomes. Identification of modifiable determinants of adolescent sleep is needed to inform prevention strategies, yet little is known about the influence of the built environment on adolescent sleep. METHODS: In this prospective study, actigraphy was used to assess sleep outcomes among 110 adolescents for 14 days each in eighth and ninth grades: duration (hours/night), onset and offset, and sleeping ≥8 hours. Home addresses were linked to built environment exposures: sound levels, tree canopy cover, street density, intersection density, population density, and housing density. Mixed-effects regression estimated associations of built environment measures with sleep outcomes, adjusting for sex, race, parent education, household income, household size, grade, weeknight status, and neighborhood poverty. RESULTS: A 1-standard deviation (SD) increase in neighborhood sound was associated with 16 minutes later sleep onset (ß = 0.28; 95% confidence interval (CI): 0.06, 0.49) and 25% lower odds of sleeping for ≥8 hours (odds ratio (OR) = 0.75, 95% CI: 0.59, 0.96). A 1-SD increase in neighborhood tree canopy was associated with 18 minutes earlier sleep onset (ß = -0.31, 95% CI: -0.49, -0.13) and 10 minutes earlier sleep offset (ß= -0.17, 95% CI: -0.28, -0.05). No associations were observed for density-based exposures. CONCLUSIONS: Higher neighborhood sound level was associated with lower odds of sufficient sleep, while higher tree canopy cover was associated with more favorable sleep timing. Neighborhood sound levels and tree canopy cover are potential targets for policies and interventions to support healthier sleep among adolescents.

Genome-wide association study implicates novel loci and reveals candidate effector genes for longitudinal pediatric bone accrual.

BACKGROUND: Bone accrual impacts lifelong skeletal health, but genetic discovery has been primarily limited to cross-sectional study designs and hampered by uncertainty about target effector genes. Here, we capture this dynamic phenotype by modeling longitudinal bone accrual across 11,000 bone scans in a cohort of healthy children and adolescents, followed by genome-wide association studies (GWAS) and variant-to-gene mapping with functional follow-up. RESULTS: We identify 40 loci, 35 not previously reported, with various degrees of supportive evidence, half residing in topological associated domains harboring known bone genes. Of several loci potentially associated with later-life fracture risk, a candidate SNP lookup provides the most compelling evidence for rs11195210 (SMC3). Variant-to-gene mapping combining ATAC-seq to assay open chromatin with high-resolution promoter-focused Capture C identifies contacts between GWAS loci and nearby gene promoters. siRNA knockdown of gene expression supports the putative effector gene at three specific loci in two osteoblast cell models. Finally, using CRISPR-Cas9 genome editing, we confirm that the immediate genomic region harboring the putative causal SNP influences PRPF38A expression, a location which is predicted to coincide with a set of binding sites for relevant transcription factors. CONCLUSIONS: Using a new longitudinal approach, we expand the number of genetic loci putatively associated with pediatric bone gain. Functional follow-up in appropriate cell models finds novel candidate genes impacting bone accrual. Our data also raise the possibility that the cell fate decision between osteogenic and adipogenic lineages is important in normal bone accrual.

Sex differences in childhood sleep and health implications.

CONTEXT: Sleep is critical for optimal childhood metabolic health and neurodevelopment. However, there is limited knowledge regarding childhood sex differences in sleep, including children with neurodevelopmental disorders, and the impact of such differences on metabolic health. OBJECTIVE: To evaluate if sex differences in childhood sleep exist and if sleep associates with metabolic health outcomes equally by sex. Using autism spectrum disorder (ASD) as a case study, we also examine sleep sex differences in children with a neurodevelopmental disorder. METHODS: A narrative review explored the literature focussing on sex differences in childhood sleep. RESULTS: Sex differences in sleep were not detected among pre-adolescents. However, female adolescents were more likely to report impaired sleep than males. Childhood obesity is more common in males. Shorter sleep duration may be associated with obesity in male pre-adolescents/adolescents; although findings are mixed. ASD is male-predominant; yet, there was an indication that pre-adolescent female children with ASD had more impaired sleep. CONCLUSION: Sex differences in sleep appear to emerge in adolescence with more impaired sleep in females. This trend was also observed among pre-adolescent female children with ASD. Further research is needed on sex differences in childhood sleep and metabolic health and the underlying mechanisms driving these differences.

Engineering a Mobile Platform to Promote Sleep in the Pediatric Primary Care Setting.

Background: Pediatricians lack tools to support families at home for the promotion of childhood sleep. We are using the Multiphase Optimization Strategy (MOST) framework to guide the development of a mobile health platform for childhood sleep promotion. Purpose: Under the preparation phase of the MOST framework, to demonstrate feasibility of a mobile health platform towards treating children with insufficient sleep. Methods: Children aged 10-12y were enrolled (Study #1: N=30; Study #2: N=43). Participants wore a sleep tracker to measure sleep duration. Data were retrieved by a mobile health platform, programmed to send introductory messages during run-in (2 weeks) and goal achievement messages during intervention (7 weeks) periods. In study #1, participants were randomized to control, gain-framed incentive or loss-framed incentive arms. In study #2, participants were randomized to control, loss-framed incentive, normative feedback or loss-framed incentive plus normative feedback arms. Results: In study #1, 1,514 nights of data were captured (69%) and sleep duration during the intervention was higher by an average of 21 (95% CI: -8, 51) and 34 (95% CI: 7, 61) minutes per night for the gain-framed and loss-framed arms, respectively, compared to controls. In study #2, 2,689 nights of data were captured (81%), with no major differences in average sleep duration between the control and the loss-framed or normative feedback arms. Conclusion: We have developed and deployed a mobile health platform that can capture sleep data and remotely communicate with families. Promising candidate intervention components will be further investigated under the optimization phase of the MOST framework.