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Aims: Fear of hypoglycaemia (FOH) can contribute to impaired sleep for adults with type 1 diabetes (T1D) and parents of children with T1D, although it is unknown how FOH may affect sleep for adolescents with T1D. This study examines the relationship between adolescent FOH and sleep and assessed the influences of continuous glucose monitor (CGM) and insulin pump use. Methods: Adolescents ages 14–18 years with T1D completed questionnaires evaluating FOH (Child Hypoglycemia Fear Survey) and sleep (Pittsburgh Sleep Quality Index, PSQI). Analyses included linear and logistic regression, t‐tests and Fisher's exact tests. Results: Participants included 95 adolescents (52 female) with a median (IQR) age of 16.5 (15.3–17.7) years and a T1D duration of 5.7 (2.5–9.6) years. Analyses showed increased FOH‐Worry subscale scores were associated with reduced sleep duration (β = −0.03, p = 0.042, adjusting for BMI z‐score, race and ethnicity) and increased sleep disturbances (OR = 1.1, p = 0.038, adjusting for race and ethnicity). Frequent CGM users had longer sleep duration (average 7.5 h) compared with infrequent or non‐CGM users (average = 6.8 h; p = 0.029), and pump users had overall improved sleep health as determined by PSQI score (p = 0.019). Technology use did not have significant interactions in the relationships between FOH and sleep duration or sleep disturbances. Conclusions: Worrying about hypoglycaemia was associated with impaired sleep for adolescents with T1D. Diabetes technology users have some sleep improvements, but CGM and pump use do little to alter the relationship between FOH and sleep outcomes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The purpose of this study was to examine the associations between sedentary behavior and moderate to vigorous physical activity (MVPA), measured by accelerometry, with body mass index (BMI) and waist circumference in 357 preschool children. Linear mixed models were used adjusting for race/ethnicity, parental education, and preschool. Follow-up analyses were performed using quantile regression. Among boys, MVPA was positively associated with BMI z-score (b = 0.080, p = .04) but not with waist circumference; quantile regression showed that MVPA was positively associated with BMI z-score at the 50th percentile (b = 0.097, p < .05). Among girls, no associations were observed between sedentary behavior and MVPA in relation to mean BMI z-score and mean waist circumference. Quantile regression indicated that, among girls at the 90th waist circumference percentile, a positive association was found with sedentary behavior (b = 0.441, p < .05), and a negative association was observed with MVPA (b = -0.599, p < .05); no associations were found with BMI z-score. In conclusion, MVPA was positively associated with BMI z-score among boys, and MVPA was negatively associated and sedentary behavior was positively associated with waist circumference among girls at the 90th percentile [ABSTRACT FROM AUTHOR]

Background: Patient safety is a national and international priority with medication safety earmarked as both a prevalent and high-risk area of concern. To date, medication safety research has focused overwhelmingly on institutional based care provided by paid healthcare professionals, which often has little applicability to the home care setting. This critical gap in our current understanding of medication safety in the home care sector is particularly evident with the elderly who often manage more than one chronic illness and a complex palette of medications, along with other care needs. This study addresses the medication management issues faced by seniors with chronic illnesses, their family, caregivers, and paid providers within Canadian publicly funded home care programs in Alberta (AB), Ontario (ON), Quebec (QC) and Nova Scotia (NS).Methods: Informed by a socio-ecological perspective, this study utilized Interpretive Description (ID) methodology and participatory photographic methods to capture and analyze a range of visual and textual data. Three successive phases of data collection and analysis were conducted in a concurrent, iterative fashion in eight urban and/or rural households in each province. A total of 94 participants (i.e., seniors receiving home care services, their family/caregivers, and paid providers) were interviewed individually. In addition, 69 providers took part in focus groups. Analysis was iterative and concurrent with data collection in that each interview was compared with subsequent interviews for converging as well as diverging patterns.Results: Six patterns were identified that provide a rich portrayal of the complexity of medication management safety in home care: vulnerabilities that impact the safe management and storage of medication, sustaining adequate supports, degrees of shared accountability for care, systems of variable effectiveness, poly-literacy required to navigate the system, and systemic challenges to maintaining medication safety in the home.Conclusions: There is a need for policy makers, health system leaders, care providers, researchers, and educators to work with home care clients and caregivers on three key messages for improvement: adapt care delivery models to the home care landscape; develop a palette of user-centered tools to support medication safety in the home; and strengthen health systems integration. [ABSTRACT FROM AUTHOR]

Background: The increasing incidence of testicular germ cell tumour (TGCT) combined with its strong heritable basis suggests that stratified screening for the early detection of TGCT may be clinically useful. We modelled the efficiency of such a personalised screening approach, based on genetic risk profiling in combination with other diagnostic tools.Methods: We compared the number of cases potentially detectable in the population under a number of screening models. The polygenic risk scoring (PRS) model was assumed to have a log-normal relative risk distribution across the 19 currently known TGCT susceptibility variants. The diagnostic performance of testicular biopsy and non-invasive semen analysis was also assessed, within a simulated combined screening programme.Results: The area under the curve for the TGCT PRS model was 0.72 with individuals in the top 1% of the PRS having a nine-fold increased TGCT risk compared with the population median. Results from population-screening simulations only achieved a maximal positive predictive value (PPV) of 60%, highlighting broader clinical factors that challenge such strategies, not least the rare nature of TGCT. In terms of future improvements, heritability estimates suggest that a significant number of additional genetic risk factors for TGCT remain to be discovered, identification of which would potentially yield improvement of the PPV to 80-90%.Conclusions: While personalised screening models may offer enhanced TGCT risk discrimination, presently the case for population-level testing is not compelling. However, future advances, such as more routine generation of whole genome data is likely to alter the landscape. More targeted screening programs may plausibly then offer clinical benefit, particularly given the significant survivorship issues associated with the successful treatment of TGCT. [ABSTRACT FROM AUTHOR]

Purpose: We aimed to determine whether baseline sedentary behavior was associated with changes in body mass index (BMI) over 9 yr. Methods: Participants were enrolled into the National Institutes of Health American Association of Retired Persons (NIH-AARP) Diet and Health study in 1995-1996 (median age, 63 yr), and BMI was reported at baseline and 9 yr later (n = 158,436). Sitting time (<3 (referent), 3-4, 5-6, 7-8, or ≥9 h•d-1), television viewing (none, <1, 1-2, 3-4, 5-6, 7-8, or ≥9 h•d-1), and the covariates (age, sex, race, education, smoking, moderate-to-vigorous physical activity, caloric intake, and sleep duration) were reported at baseline. We used longitudinal quantile regression to model changes at the 10th, 25th, 50th, 75th, and 90th BMI percentiles. Results: More sitting at baseline was associated with additional increases in BMI over time, and the association was stronger at the upper BMI percentiles (e.g., <3 (referent) vs 5-6 h•d-1 of sitting additional increases: 50th percentile = 0.41 kg•m-2 and 95% confidence interval (CI) = 0.34-0.48; 90th percentile = 0.85 kg•m-2 and 95% CI = 0.72-0.98). Similar associations were observed between more television viewing at baseline and additional increases in BMI over time (e.g., no television (referent) vs 3-4 h•d-1 of television: 50th percentile = 1.96 kg•m-2 and 95% CI = 1.77-2.15; 90th percentile = 2.11 kg•m-2 and 95% CI = 1.49-2.73). Conclusions: Reducing sedentary behavior could help prevent an increase in BMI in adulthood especially at the upper percentiles of the BMI distribution and thereby reduce the prevalence of obesity. [ABSTRACT FROM AUTHOR]

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]) (β = 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. [ABSTRACT FROM AUTHOR]

BACKGROUND: Weight-for-length (WFL) is currently used to assess adiposity under 2 years. We assessed WFL- versus BMI-based estimates of adiposity in healthy infants in determining risk for early obesity. METHODS: Anthropometrics were extracted from electronic medical records for well-child visits for 73 949 full-term infants from a large pediatric network. World Health Organization WFL and BMI z scores (WFL-z and BMI-z, respectively) were calculated up to age 24 months. Correlation analyses assessed the agreement between WFL-z and BMI-z and within-subject tracking over time. Logistic regression determined odds of obesity at 2 years on the basis of adiposity classification at 2 months. RESULTS: Agreement between WFL-z and BMI-z increased from birth to 6 months and remained high thereafter. BMI-z at 2 months was more consistent with measurements at older ages than WFL-z at 2 months. Infants with high BMI (≥85th percentile) and reference WFL (5th-85th percentiles) at 2 months had greater odds of obesity at 2 years than those with high WFL (≥85th percentile) and reference BMI (5th-85th percentiles; odds ratio, 5.49 vs 1.40; P < .001). At 2 months, BMI had a higher positive predictive value than WFL for obesity at 2 years using cut-points of either the 85th percentile (31% vs 23%) or 97.7th percentile (47% vs 29%). CONCLUSIONS: High BMI in early infancy is more strongly associated with early childhood obesity than high WFL. Forty-seven percent of infants with BMI ≥97.7th percentile at 2 months (versus 29% of infants with WFL ≥97.7th percentile at 2 months) were obese at 2 years. Epidemiologic studies focused on assessing childhood obesity risk should consider using BMI in early infancy. [ABSTRACT FROM AUTHOR]