Losing sleep influences dietary intake in children: a longitudinal compositional analysis of a randomised crossover trial.

BACKGROUND: Although inadequate sleep increases the risk of obesity in children, the mechanisms remain unclear. The aims of this study were to assess how sleep loss influenced dietary intake in children while accounting for corresponding changes in sedentary time and physical activity; and to investigate how changes in time use related to dietary intake. METHODS: A randomized crossover trial in 105 healthy children (8-12 years) with normal sleep (~ 8-11 h/night) compared sleep extension (asked to turn lights off one hour earlier than usual for one week) and sleep restriction (turn lights off one hour later) conditions, separated by a washout week. 24-h time-use behaviors (sleep, wake after sleep onset, physical activity, sedentary time) were assessed using waist-worn actigraphy and dietary intake using two multiple-pass diet recalls during each intervention week. Longitudinal compositional analysis was undertaken with mixed effects regression models using isometric log ratios of time use variables as exposures and dietary variables as outcomes, and participant as a random effect. RESULTS: Eighty three children (10.2 years, 53% female, 62% healthy weight) had 47.9 (SD 30.1) minutes less sleep during the restriction week but were also awake for 8.5 (21.4) minutes less at night. They spent this extra time awake in the day being more sedentary (+ 31 min) and more active (+ 21 min light physical activity, + 4 min MVPA). After adjusting for all changes in 24-h time use, losing 48 min of sleep was associated with consuming significantly more energy (262 kJ, 95% CI:55,470), all of which was from non-core foods (314 kJ; 43, 638). Increases in sedentary time were related to increased energy intake from non-core foods (177 kJ; 25, 329) whereas increases in MVPA were associated with higher intake from core foods (72 kJ; 7,136). Changes in diet were greater in female participants. CONCLUSION: Loss of sleep was associated with increased energy intake, especially of non-core foods, independent of changes in sedentary time and physical activity. Interventions focusing on improving sleep may be beneficial for improving dietary intake and weight status in children. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ANZCTR ACTRN12618001671257, Registered 10th Oct 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=367587&isReview=true.

Protocol for a prospective, multicenter, parallel-group, open-label randomized controlled trial comparing standard care with Closed lOoP In chiLdren and yOuth with Type 1 diabetes and high-risk glycemic control: the CO-PILOT trial.

Purpose: Advanced hybrid closed loop (AHCL) systems have the potential to improve glycemia and reduce burden for people with type 1 diabetes (T1D). Children and youth, who are at particular risk for out-of-target glycemia, may have the most to gain from AHCL. However, no randomized controlled trial (RCT) specifically targeting this age group with very high HbA1c has previously been attempted. Therefore, the CO-PILOT trial (Closed lOoP In chiLdren and yOuth with Type 1 diabetes and high-risk glycemic control) aims to evaluate the efficacy and safety of AHCL in this group. Methods: A prospective, multicenter, parallel-group, open-label RCT, comparing MiniMed™ 780G AHCL to standard care (multiple daily injections or continuous subcutaneous insulin infusion). Eighty participants aged 7-25 years with T1D, a current HbA1c ≥ 8.5% (69 mmol/mol), and naïve to automated insulin delivery will be randomly allocated to AHCL or control (standard care) for 13 weeks. The primary outcome is change in HbA1c between baseline and 13 weeks. Secondary outcomes include standard continuous glucose monitor glycemic metrics, psychosocial factors, sleep, platform performance, safety, and user experience. This RCT will be followed by a continuation phase where the control arm crosses over to AHCL and all participants use AHCL for a further 39 weeks to assess longer term outcomes. Conclusion: This study will evaluate the efficacy and safety of AHCL in this population and has the potential to demonstrate that AHCL is the gold standard for children and youth with T1D experiencing out-of-target glucose control and considerable diabetes burden. Trial registration: This trial was prospectively registered with the Australian New Zealand Clinical Trials Registry on 14 November 2022 (ACTRN12622001454763) and the World Health Organization International Clinical Trials Registry Platform (Universal Trial Number U1111-1284-8452). Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-024-01397-4.

Equations to estimate human milk intake in infants aged 7 to 10 months: prediction models from a cross-sectional study.

BACKGROUND: Obtaining valid estimates of nutrient intake in infants is currently limited by the difficulties of accurately measuring human milk intake. Current methods are either unsuitable for large-scale studies (i.e., the gold standard dose-to-mother stable isotope technique) or use set amounts, regardless of known variability in individual intake. OBJECTIVES: This cross-sectional study aimed to develop equations to predict human milk intake using simple measures and to carry out external validation of existing methods against the gold standard technique. METHODS: Data on human milk intake were obtained using the dose-to-mother stable isotope technique in 157 infants aged 7-10 mo and their mothers. Predictive equations were developed using questionnaire and anthropometric data (Model 1) and additional dietary data (Model 2) using lasso regression. Bland-Altman plots and intraclass correlation coefficients (ICC) also assessed the validity of existing methods (FITS and ALSPAC studies). RESULTS: The strongest univariate predictors of human milk intake in infants of 8.3 mo on average (46% female) were infant age, infant body mass index (BMI), number of breastfeeds a day, infant formula consumption, and energy from complementary food intake. Mean [95% confidence interval (CI)] differences in predicted versus measured human milk intake [mean (SD): 762 (257) mL/day] were 0.0 mL/day (-26, 26) for Model 1 (ICC 0.74) and 0.5 mL/day (-21, 22) for Model 2 (ICC 0.83). Corresponding differences were -197 mL/day (-233, -161; ICC 0.32) and -175 mL/day (-216, -134; ICC 0.41) for the methods used by FITS and ALSPAC, respectively. CONCLUSIONS: The Human Milk Intake Level Calculation provides substantial improvements on existing methods to estimate human milk intake in infants aged 7-10 mo, while utilizing data commonly collected in nutrition surveys. Although further validation in an external sample is recommended, these equations can be used to estimate human milk intake at this age with some confidence. This clinical trial was registered at http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=379436) as ACTRN12620000459921.

Baby Food Pouches, Baby-Led Weaning, and Iron Status in New Zealand Infants: An Observational Study.

Iron deficiency in infants can impact development, and there are concerns that the use of baby food pouches and baby-led weaning may impair iron status. First Foods New Zealand (FFNZ) was an observational study of 625 New Zealand infants aged 6.9 to 10.1 months. Feeding methods were defined based on parental reports of infant feeding at "around 6 months of age": "frequent" baby food pouch use (five+ times per week) and "full baby-led weaning" (the infant primarily self-feeds). Iron status was assessed using a venepuncture blood sample. The estimated prevalence of suboptimal iron status was 23%, but neither feeding method significantly predicted body iron concentrations nor the odds of iron sufficiency after controlling for potential confounding factors including infant formula intake. Adjusted ORs for iron sufficiency were 1.50 (95% CI: 0.67-3.39) for frequent pouch users compared to non-pouch users and 0.91 (95% CI: 0.45-1.87) for baby-led weaning compared to traditional spoon-feeding. Contrary to concerns, there was no evidence that baby food pouch use or baby-led weaning, as currently practiced in New Zealand, were associated with poorer iron status in this age group. However, notable levels of suboptimal iron status, regardless of the feeding method, emphasise the ongoing need for paying attention to infant iron nutrition.

Improved glycaemic control induced by evening activity breaks does not persist overnight amongst healthy adults: A randomized crossover trial.

AIMS: To compare the effects of 4 hours of laboratory-based regular activity breaks (RABs) and prolonged sitting (SIT) on subsequent 48-h free-living interstitial glucose levels in a group of healthy adults. MATERIALS AND METHODS: In this randomized crossover trial, participants completed two 4-h laboratory-based interventions commencing at ~5:00 pm: (1) SIT and (2) SIT interrupted with 3 min of body weight resistance exercise activity breaks every 30 min (RABs). Continuous glucose monitoring was performed during the intervention and for 48-h after, during which time participants returned to a free-living setting. RESULTS: Twenty-eight adults (female n = 20, mean ± SD age 25.5 ± 5.6 years, body mass index 29.2 ± 6.9 kg/m2) provided data for this analysis. During the intervention period, RABs lowered mean interstitial glucose by 8.3% (-0.47 mmol/L/4 h, 95% confidence interval [CI] -0.74 to -0.20; p = 0.001) and area under the curve (AUC) by 8.9% (-2.01 mmol/L/4 h, 95% CI -3.05 to -0.97; p < 0.001) compared to SIT. Measures of glycaemic variability were not significantly different during the intervention. There were no significant differences in mean glucose and AUC between conditions during the first nocturnal period and 24-h post intervention. When compared to SIT, RABs increased continuous overall net action of glucose at 1 h and SD glucose by 22% (0.18 mmol/L, 95% CI 0.03 to 0.29; p = 0.018) and 26% (95% CI 4.9 to 42.7; p = 0.019) in the first nocturnal period and by 10% (0.09 mmol/L, 95% CI 0.01, 0.17; p = 0.025) and 15% (95% CI 6.6 to 22.4; p = 0.001) in the 24-h post intervention period, respectively. CONCLUSION: Performing activity breaks in the evening results in acute reductions in interstitial glucose concentrations; however, the magnitude of these changes is not maintained overnight or into the following 48 hours.

Contribution of Infant Food Pouches and Other Commercial Infant Foods to the Diets of Infants: A Cross-sectional Study.

BACKGROUND: Although considerable concern has been expressed about the nutritional implications of infant food pouches, how they impact infant diet has not been examined. OBJECTIVES: The objective of this study was to determine the contribution of infant food pouches specifically, and commercial infant foods generally, to nutrient intake from complementary foods in infants. METHODS: Two multiple-pass 24-h diet recall data were collected from 645 infants (6.0-11.9 mo) in the First Foods and Young Foods New Zealand studies. Detailed information was obtained on commercial infant food use, including pouches, and nutrient composition was calculated through recipe modeling. RESULTS: The diverse sample (46.1% female; 21.1% Maori, 14.1% Asian, and 54.6% European) was aged (SD) 8.4 (0.9) mo. More than one-quarter of households had high socioeconomic deprivation. Almost half (45.3%) of infants consumed an infant food pouch on ≥1 recall day [mean (SD), 1.3 (0.9) times/d], obtaining 218 (124) kJ of energy on each eating occasion. Comparable numbers for all commercial infant and toddler foods (CITFs) were 78.0%, contributing 2.2 (1.6) and 140 (118) kJ of energy. Infant food pouches provided 25.5% of the total energy from complementary foods in those infants who consumed pouches on the recall days but just 11% in all infants. Median percentage contribution of infant food pouches to nutrient intake from complementary foods in consumers ranged from <1% (added sugars and retinol) to >30% (carbohydrate, total sugars, fiber, vitamin A, and vitamin C). CITF contributed 21.4% of energy from complementary foods for infant consumers, with median percentage contribution ranging from 0.1% (retinol) to 40.3% (iron). CONCLUSIONS: Infant food pouches make relatively small contributions to energy intake in infants but are important sources of carbohydrates, fiber, and vitamins A, C, and B-6. Almost half of the total sugars consumed from complementary foods is provided by these pouches. This trial was registered at the Australian New Zealand Clinical Trials Registry as ACTRN12620000459921.

Comparing the glycaemic outcomes between real-time continuous glucose monitoring (rt-CGM) and intermittently scanned continuous glucose monitoring (isCGM) among adults and children with type 1 diabetes: A systematic review and meta-analysis of randomized controlled trials.

AIM: To conduct a systematic review and meta-analysis of randomized controlled trials (RCTs) comparing the effectiveness of real-time continuous glucose monitoring (rtCGM) versus intermittently scanned continuous glucose monitoring (isCGM) on key glycaemic metrics (co-primary outcomes HbA1c and time-in-range [TIR] 70-180 mg/dL, 3.9-10.0 mmol/L) among people with type 1 diabetes (T1D). METHODS: Medline, PubMed, Scopus, Web of Science and Cochrane Central Register of clinical trials were searched. Inclusion criteria were RCTs; T1D populations of any age and insulin regimen; comparing any type of rtCGM with isCGM (only the first generation had been compared to date); and reporting the glycaemic outcomes. Glycaemic outcomes were extracted post-intervention and expressed as mean differences and 95% CIs between the two comparators. Results were pooled using a random-effect meta-analysis. The risk of bias was assessed using the Cochrane RoB2 tool. The quality of evidence was assessed by the GRADE approach. RESULTS: Five RCTs met the inclusion criteria (4 parallel and 1 crossover design; 4 with CGM use <8 weeks), involving 446 participants (354 adults; 92 children and adolescents). Overall, meta-analysis showed rtCGM compared to isCGM improved absolute TIR by +7.0% (95% CI: 5.8%-8.3%, I2 = 0%, p < 0.01) accompanied by a favorable effect on time-below-range <70 mg/dL (3.9 mmol/L) - 1.7% (95%CI: -3.0% to -0.4%; p = 0.03). No differences were seen regarding HbA1c. CONCLUSIONS: This meta-analysis highlights that for people with T1D, rtCGM confers benefits over isCGM primarily related to increased TIR, with improvements in hypo- and hyperglycaemia.

Smartphone survey data reveal the timecourse of changes in mood outcomes following vitamin C or kiwifruit intervention in adults with low vitamin C.

Vitamin C-rich foods can improve mood; however, the timecourse of these benefits is unknown. This study utilised intensive longitudinal smartphone surveys from a three-armed placebo-controlled trial to determine mood-related changes following supplementation with vitamin C (250 mg tablet/d), kiwifruit (2 SunGold™ kiwifruit/d) or a placebo (1 tablet/d). Secondary data were analysed from the KiwiC for Vitality trial (Trial ID: ACTRN12617001031358). Adults (n 155, 63 % female, aged 18-35 years) with low plasma vitamin C (<40 µmol/l) completed a 14-d lead-in, 28-d intervention and 14-d washout. Participants self-reported vitality (SF-36), mood (POMS total mood disturbance), flourishing (flourishing scale), sleep quality, sleep quantity and physical activity every second day using smartphone surveys. Plasma vitamin C, measured fortnightly, reached saturation after 2 weeks of vitamin C or kiwifruit supplementation. Kiwifruit supplementation improved vitality and mood within 4 days, peaking around 14-16 days, and improved flourishing from day 14. Vitamin C marginally improved mood until day 12. Incremental AUC analyses revealed significant overall effects of kiwifruit consumption on vitality and mood compared with placebo, which were stronger than effects for vitamin C tablets, but attenuated when adjusting for covariates. Sensitivity analyses of participants with low baseline vitamin C status revealed improved mood (vitamin C and kiwifruit) and flourishing (kiwifruit only). This is the first study to use intensive smartphone surveys to model the day-to-day timecourse of mood-related states following vitamin C intervention and highlights the value of using smartphone surveys to reveal the temporal changes in mood-related outcomes following nutrient supplementation.

Glucose and Psychosocial Outcomes 12 Months Following Transition from Multiple Daily Injections to Advanced Hybrid Closed Loop in Youth with Type 1 Diabetes and Suboptimal Glycemia.

Objective: To investigate 12-month glycemic and psychosocial changes following transition from multiple daily injections (MDI) to advanced hybrid closed-loop (AHCL) therapy in youth (aged 13-25 years) with type 1 diabetes and suboptimal glycemia (glycated hemoglobin [HbA1c] ≥8.5% [69 mmol/mol]). Research Design and Methods: Prospective, single arm, dual-center study in 20 participants. Extension phase outcomes reported after 12 months, including HbA1c, time in glycemic ranges, AHCL system performance, and psychosocial questionnaires assessing quality of life, diabetes treatment, and sleep. Results: After 12 months, 19 out of 20 participants continued to use AHCL. Average time-in-range 70-180 mg/dL (3.9-10.0 mmol/L) improved from 27.6% ± 13.2% to 62.5% ± 11.4%. This translated to an average 2.5 percentage-point (27.1 mmol/mol) improvement in HbA1c from 10.5% ± 2.1% (91.2 mmol/mol) at baseline to 8.0% ± 0.9% (64.1 mmol/mol) at 12 months. Psychosocial questionnaires and very high HbA1c at study entry indicated significant diabetes-associated burden for both individuals and parents. After 12 months, improvements were observed in general and diabetes-specific health-related quality of life, as well as in diabetes treatment satisfaction. Safety data were reassuring with a diabetic ketoacidosis rate of 0.15 per participant-year after 12 months of AHCL (compared to 0.25 per participant-year in the 12 months before the study). Conclusions: After 12 months of AHCL usage, this study highlights the potential for substantial and sustained glycemic and psychosocial improvements among individuals experiencing considerable diabetes burden and suboptimal glycemia, following their switch from MDI to AHCL.

Baby food pouches and Baby-Led Weaning: Associations with energy intake, eating behaviour and infant weight status.

Although concern is frequently expressed regarding the potential impact of baby food pouch use and Baby-Led Weaning (BLW) on infant health, research is scarce. Data on pouch use, BLW, energy intake, eating behaviour and body mass index (BMI) were obtained for 625 infants aged 7-10 months in the First Foods New Zealand study. Frequent pouch use was defined as ≥5 times/week during the past month. Traditional spoon-feeding (TSF), "partial" BLW and "full" BLW referred to the relative proportions of spoon-feeding versus infant self-feeding, assessed at 6 months (retrospectively) and current age. Daily energy intake was determined using two 24-h dietary recalls, and caregivers reported on a variety of eating behaviours. Researchers measured infant length and weight, and BMI z-scores were calculated (World Health Organization Child Growth Standards). In total, 28% of infants consumed food from pouches frequently. Frequent pouch use was not significantly related to BMI z-score (mean difference, 0.09; 95% CI -0.09, 0.27) or energy intake (92 kJ/day; -19, 202), but was associated with greater food responsiveness (standardised mean difference, 0.3; 95% CI 0.1, 0.4), food fussiness (0.3; 0.1, 0.4) and selective/restrictive eating (0.3; 0.2, 0.5). Compared to TSF, full BLW was associated with greater daily energy intake (BLW at 6 months: mean difference 150 kJ/day; 95% CI 4, 297; BLW at current age: 180 kJ/day; 62, 299) and with a range of eating behaviours, including greater satiety responsiveness, but not BMI z-score (6 months: 0.06 (-0.18, 0.30); current age: 0.06 (-0.13, 0.26)). In conclusion, neither feeding approach was associated with weight in infants, despite BLW being associated with greater energy intake compared with TSF. However, infants who consumed pouches frequently displayed higher food fussiness and more selective eating.

Micronutrient status of New Zealand adolescent women consuming vegetarian and non-vegetarian diets.

BACKGROUND AND OBJECTIVES: Globally, there appears to be an ever-increasing interest in adopting a vegetarian diet. However, there are concerns that avoiding meat may increase the risk of anaemia and micronutrient deficiencies, especially for vulnerable populations, such as adolescent women. The objective of this study was to compare the micronutrient status of vegetarian and non-vegetarian adolescent women in New Zealand. METHODS AND STUDY DESIGN: Adolescent women aged 15-18 y were recruited from eight locations across New Zealand. Blood samples were analysed for: haemoglobin, serum ferritin, soluble transferrin receptor, zinc, selenium, retinol binding protein, folate, vitamin B-12, vitamin D and parathyroid hormone. RESULTS: Of the 182 participants who provided a blood sample, 15% self-identified as vegetarian (n=27). On average, vegetarians had 3.1% (95% CI -5.8 to -0.4, p=0.025) lower haemoglobin, and 8.3% (95%CI -14.1 to -2.1, p=0.004) lower selenium. In contrast, serum folate was 80.5% (95% CI 45.7 to 123.7, p<0.001) higher. The prevalence of zinc and selenium deficiency was higher among vegetarians (50% and 12%, respectively) than non-vegetarians (21%, and 2%, respectively). CONCLUSIONS: Adolescent vegetarian women may be at increased risk of deficiency of micronutrients commonly found in animal products, including zinc and selenium, and may benefit from following dietary practices that enhance micronutrient intake and absorption.

Predictors for achieving optimal sleep in healthy children: Exploring sleep patterns in a sleep extension trial.

STUDY OBJECTIVES: Earlier bedtimes can help some children get more sleep, but we don't know which children, or what features of their usual sleep patterns could predict success with this approach. Using data from a randomized crossover trial of sleep manipulation, we sought to determine this. METHODS: Participants were 99 children aged 8-12years (49.5% female) with no sleep disturbances. Sleep was measured by actigraphy at baseline and over a restriction or extension week (1 hour later or earlier bedtime respectively), randomly allocated and separated by a washout week. Data were compared between baseline (week 1) and extension weeks only (week 3 or 5), using linear or logistic regression analyses as appropriate, controlling for randomization order. RESULTS: One hour less total sleep time than average at baseline predicted 29.7 minutes (95% CI: 19.4, 40.1) of sleep gained and 3.45 (95% CI: 1.74, 6.81) times higher odds of successfully extending sleep by >30 minutes. Per standardized variable, less total sleep time and a shorter sleep period time were the strongest predictors (significant odds ratios (ORs) of 2.51 and 2.28, respectively). Later sleep offset, more variability in sleep timing and lower sleep efficiency also predicted sleep gains. The sleep period time cut-point that optimized prediction of successful sleep gains was <8 hours 28 minutes with 75% of children's baseline sleep in that range. CONCLUSIONS: Children with a baseline sleep period time <8½ hours a night obtained the most sleep from earlier bedtimes maintained over a week, demonstrating experimentally the value of earlier bedtimes to improve sleep. CLINICAL TRIALS REGISTRY: Australian New Zealand Clinical Trial Registry, ACTRN12618001671257, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=367587&isReview=true.

Rapid infant weight gain or point-in-time weight status: Which is the best predictor of later obesity and body composition?

OBJECTIVE: The aim of this study was to determine which growth indicator (weight, weight-for-length, BMI) and time frame (6- or 12-month intervals between 0 and 24 months) of rapid infant weight gain (RIWG) best predicted obesity risk and body composition at 11 years of age. METHODS: RIWG (increase ≥0.67 z scores between two time points) was calculated from weight and length/height at birth, 0.5, 1, 1.5, and 2 years. The predictive value of each measure and time frame was calculated in relation to obesity (BMI ≥95th percentile) and body fat (fat mass index [FMI], dual-energy X-ray absorptiometry scan) at 11 years. RESULTS: The sensitivity (1.5% to 62.1%) and positive predictive value (12.5% to 33.3%) of RIWG to predict obesity varied considerably. Having obesity at any time point appeared a stronger risk factor than any indicator of RIWG for obesity at 11 years. Obesity at any age during infancy consistently predicted a greater FMI of around 1.1 to 1.5 kg/m2 at 11 years, whereas differences for RIWG were inconsistent. CONCLUSIONS: A simple measure of obesity status at a single time point between 6 and 24 months of age appeared a stronger risk factor for later obesity and FMI than RIWG assessed by any indicator, over any time frame.

Development of a Protocol for Objectively Measuring Digital Device Use in Youth.

INTRODUCTION: Screen time is predominantly measured using questionnaires assessing a limited range of activities. This project aimed to develop a coding protocol that reliably identified screen time, including device type and specific screen behaviors, from video-camera footage. METHODS: Screen use was captured from wearable and stationary PatrolEyes video cameras in 43 participants (aged 10-14 years) within the home environment (May-December 2021, coding in 2022, statistical analysis in 2023). After extensive piloting, the inter-rater reliability of the final protocol was determined in 4 coders using 600 minutes of footage from 18 participants who spent unstructured time on digital devices. Coders independently annotated all footage to determine 8 device types (e.g., phone, TV) and 9 screen activities (e.g., social media, video gaming) using Observer XT (behavioral coding software). Reliability was calculated using weighted Cohen's κ for duration per sequence (meets criteria for total time in each category) and frequency per sequence (meets criteria for total time in each category and order of use) for every coder pair on a per-participant and footage type basis. RESULTS: Overall reliability of the full protocol was excellent (≥0.8) for both duration per sequence (κ=0.89-0.93) and the more conservative frequency per sequence (κ=0.83-0.86) analyses. This protocol reliably differentiates between different device types (κ=0.92-0.94) and screen behaviors (κ=0.81-0.87). Coder agreement ranged from 91.7% to 98.8% across 28.6-107.3 different instances of screen use. CONCLUSIONS: This protocol reliably codes screen activities in adolescents, offering promise for improving the understanding of the impact of different screen activities on health.

The effect of modest changes in sleep on dietary intake and eating behavior in children: secondary outcomes of a randomized crossover trial.

BACKGROUND: Insufficient sleep duration increases obesity risk in children, but the mechanisms remain unclear. OBJECTIVES: This study seeks to determine how changes in sleep influence energy intake and eating behavior. METHODS: Sleep was experimentally manipulated in a randomized, crossover study in 105 children (8-12 y) who met current sleep guidelines (8-11 h/night). Participants went to bed 1 h earlier (sleep extension condition) and 1 h later (sleep restriction condition) than their usual bedtime for 7 consecutive nights, separated by a 1-wk washout. Sleep was measured via waist-worn actigraphy. Dietary intake (2 24-h recalls/wk), eating behaviors (Child Eating Behavior Questionnaire), and the desire to eat different foods (questionnaire) were measured during or at the end of both sleep conditions. The type of food was classified by the level of processing (NOVA) and as core or noncore (typically energy-dense foods) foods. Data were analyzed according to 'intention to treat' and 'per protocol,' an a priori difference in sleep duration between intervention conditions of ≥30 min. RESULTS: The intention to treat analysis (n = 100) showed a mean difference (95% CI) in daily energy intake of 233 kJ (-42, 509), with significantly more energy from noncore foods (416 kJ; 6.5, 826) during sleep restriction. Differences were magnified in the per-protocol analysis, with differences in daily energy of 361 kJ (20, 702), noncore foods of 504 kJ (25, 984), and ultraprocessed foods of 523 kJ (93, 952). Differences in eating behaviors were also observed, with greater emotional overeating (0.12; 0.01, 0.24) and undereating (0.15; 0.03, 0.27), but not satiety responsiveness (-0.06; -0.17, 0.04) with sleep restriction. CONCLUSIONS: Mild sleep deprivation may play a role in pediatric obesity by increasing caloric intake, particularly from noncore and ultraprocessed foods. Eating in response to emotions rather than perceived hunger may partly explain why children engage in unhealthy dietary behaviors when tired. This trial was registered at Australian New Zealand Clinical Trials Registry; ANZCTR as CTRN12618001671257.

Effect of Sleep Changes on Health-Related Quality of Life in Healthy Children: A Secondary Analysis of the DREAM Crossover Trial.

Importance: Little is known regarding the effect of poor sleep on health-related quality of life (HRQOL) in healthy children. Objective: To determine the effect of induced mild sleep deprivation on HRQOL in children without major sleep issues. Design, Setting, and Participants: This prespecified secondary analysis focused on HRQOL, a secondary outcome of the Daily Rest, Eating, and Activity Monitoring (DREAM) randomized crossover trial of children who underwent alternating weeks of sleep restriction and sleep extension and a 1-week washout in between. The DREAM trial intervention was administered at participants' homes between October 2018 and March 2020. Participants were 100 children aged 8 to 12 years who lived in Dunedin, New Zealand; had no underlying medical conditions; and had parent- or guardian-reported normal sleep (8-11 hours/night). Data were analyzed between July 4 and September 1, 2022. Interventions: Bedtimes were manipulated to be 1 hour later (sleep restriction) and 1 hour earlier (sleep extension) than usual for 1 week each. Wake times were unchanged. Main Outcomes and Measures: All outcome measures were assessed during both intervention weeks. Sleep timing and duration were assessed using 7-night actigraphy. Children and parents rated the child's sleep disturbances (night) and impairment (day) using the 8-item Pediatric Sleep Disturbance and 8-item Sleep-Related Impairment scales of the Patient-Reported Outcomes Measurement Information System questionnaire. Child-reported HRQOL was assessed using the 27-item KIDSCREEN questionnaire with 5 subscale scores and a total score. Both questionnaires assessed the past 7 days at the end of each intervention week. Data were presented as mean differences and 95% CIs between the sleep restriction and extension weeks and were analyzed using intention to treat and an a priori difference in sleep of at least 30 minutes per night. Results: The final sample comprised 100 children (52 girls [52%]; mean [SD] age, 10.3 [1.4] years). During the sleep restriction week, children went to sleep 64 (95% CI, 58-70) minutes later, and sleep offset (wake time) was 18 (95% CI, 13-24) minutes later, meaning that children received 39 (95% CI, 32-46) minutes less of total sleep per night compared with the sleep extension week in which the total sleep time was 71 (95% CI, 64-78) minutes less in the per-protocol sample analysis. Both parents and children reported significantly less sleep disturbance at night but greater sleep impairment during the day with sleep restriction. Significant standardized reductions in physical well-being (standardized mean difference [SMD], -0.28; 95% CI, -0.49 to -0.08), coping in a school environment (SMD, -0.26; 95% CI, -0.42 to -0.09), and total HRQOL score (SMD, -0.21; 95% CI, -0.34 to -0.08) were reported by children during sleep restriction, with an additional reduction in social and peer support (SMD, -0.24; 95% CI, -0.47 to -0.01) in the per-protocol sample analysis. Conclusions and Relevance: Results of this secondary analysis of the DREAM trial indicated that even 39 minutes less of sleep per night for 1 week significantly reduced several facets of HRQOL in children. This finding shows that ensuring children receive sufficient good-quality sleep is an important child health issue. Trial Registration: Australian New Zealand Clinical Trials Registry: ACTRN12618001671257.

Breaking Up Evening Sitting with Resistance Activity Improves Postprandial Glycemic Response: A Randomized Crossover Study.

INTRODUCTION: Interrupting sedentary time during the day reduces postprandial glycemia (a risk factor for cardiometabolic disease). However, it is not known if benefits exist for postprandial glucose, insulin and triglyceride responses in the evening, and if these benefits differ by body mass index (BMI) category. METHODS: In a randomized crossover study, 30 participants (25.4 ± 5.4 yr old; BMI 18.5-24.9: n = 10, BMI 25-29.9: n = 10, BMI ≥30: n = 10) completed two intervention arms, beginning at ~1700 h: prolonged sitting for 4 h, and sitting with regular activity breaks of 3 min of resistance exercises every 30 min. Plasma glucose, insulin, and triglyceride concentrations were measured in response to two meals fed at baseline and 120 min. Four-hour incremental area under the curve was compared between interventions. Moderation by BMI status was explored. RESULTS: Overall, when compared with prolonged sitting, regular activity breaks lowered plasma glucose and insulin incremental area under the curve by 31.5% (95% confidence interval = -49.3% to -13.8%) and 26.6% (-39.6% to -9.9%), respectively. No significant differences were found for plasma triglyceride area under the curve. Interactions between BMI status and intervention was not statistically significant. CONCLUSIONS: Interventions that interrupt sedentary time in the evening may improve cardiometabolic health by some magnitude in all participants regardless of bodyweight.

Prevalence of low and high BMI during the first 3 years of life: using New Zealand national electronic health data.

BACKGROUND: Data on body mass index (BMI) in infants and toddlers worldwide are lacking, relative to older age groups. OBJECTIVES: To describe the growth (weight, length/height, head circumference, and BMI z-score) of New Zealand children under the age of 3 years, and examine differences by sociodemographic characteristics (sex, ethnicity, and deprivation). METHODS: Electronic health data were collected by Whanau Awhina Plunket, who provide free 'Well Child' services for approximately 85% of newborn babies in New Zealand. Data from children under the age of 3, who had their weight and length/height measured between 2017 and 2019, were included. The prevalence of BMI (WHO child growth standards) ≤2nd, ≥85th, and ≥95th percentiles were determined. RESULTS: Between 12 weeks and 27 months of age, the percentage of infants ≥85th BMI percentile increased from 10.8% (95% CI, 10.4%-11.2%) to 35.0% (34.2%-35.9%). The percentage of infants with high BMI (≥95th percentile) also increased, particularly between 6 months (6.4%; 95% CI, 6.0%-6.7%) and 27 months (16.4%; 15.8%-17.1%). By contrast, the percentage of infants with low BMI (≤2nd percentile) appeared steady between 6 weeks and 6 months, and declined at older ages. The prevalence of infants with a high BMI appears to increase substantially from 6 months across sociodemographic characteristics, with a widening prevalence gap by ethnicity occurring from 6 months, mirroring that of infants with a low BMI. CONCLUSIONS: The number of children with high BMI increases rapidly between 6 months and 27 months of age, suggesting this is an important timeframe for monitoring and preventive action. Future work should investigate the longitudinal growth trajectories of these children to determine if any particular patterns predict later obesity and what strategies could effectively change them.

Impact of Advanced Hybrid Closed Loop on Youth With High-Risk Type 1 Diabetes Using Multiple Daily Injections.

OBJECTIVE: To evaluate glycemic outcomes in youth (aged 13-25 years) with type 1 diabetes and high-risk glycemic control (HbA1c ≥8.5% [69 mmol/mol]) on multiple daily injection (MDI) therapy after transitioning to advanced hybrid closed loop (AHCL) therapy. RESEARCH DESIGN AND METHODS: This prospective, 3-month, single-arm, dual-center study enrolled 20 participants, and all completed the study. RESULTS: HbA1c decreased from 10.5 ± 2.1% (91.2 ± 22.8 mmol/mol) at baseline to 7.6 ± 1.1% (59.7 ± 11.9 mmol/mol), and time spent in target range 70-180 mg/dL (3.9-10.0 mmol/L) increased from 27.6 ± 13.2% at baseline to 66.5 ± 9.8% after 3 months of AHCL. Two episodes of diabetic ketoacidosis attributed to infusion set failure occurred. CONCLUSIONS: AHCL has the potential to improve suboptimal glycemia in youth with type 1 diabetes previously on MDI therapy.

Where does the time go when children don't sleep? A randomized crossover study.

OBJECTIVE: This study aimed to describe how mild sleep deprivation in children changes time spent physically active and sedentary. METHODS: In 2018 through 2020, children (n = 105) with normal sleep were randomized to go to bed 1 hour earlier (extension) or 1 hour later (restriction) than their usual bedtime for 1 week, each separated by a 1-week washout. Twenty-four-hour movement behaviors were measured with waist-worn actigraphy and expressed in minutes and proportions (percentages). Mixed-effects regression models determined mean differences in time use (95% CI) between conditions. Time gained from sleep lost that was reallocated to other movement behaviors in the 24-hour day was modeled using regression. RESULTS: Children (n = 96) gained ~49 minutes of awake time when sleep was restricted compared with extended. This time was mostly reallocated to sedentary behavior (28 minutes; 95% CI: 19-37), followed by physical activity (22 minutes; 95% CI: 14-30). When time was expressed as a percentage, the overall composition of movement behavior remained similar across both sleep conditions. CONCLUSIONS: Children were not less physically active when mildly sleep deprived. Time gained from sleeping less was proportionally, rather than preferentially, reallocated to sedentary time and physical activity. These findings suggest that decreased physical activity seems unlikely to explain the association between short sleep and obesity in children.