Pediatric Obesity最新文献

Background

American Indian youth experience a high risk of overweight/obesity and type 2 diabetes.

Objectives

To evaluate the effect of a behavioural intervention on diabetes risk factors among American Indian youth with overweight/obesity.

Methods

Between 2018 and 2023, youth (7–10 years) were randomised to the tribal turning point (TTP) intervention (n = 87) or control arm (n = 95). Community coaches delivered the core intervention in the first 6 months (10 group classes, 4 individual sessions with motivational interviewing) followed by the booster intervention in the second 6 months (2 group classes, 3 individual sessions). The control arm received 4 health/safety classes over 12 months. Data were collected at baseline, 6, and 12 months. Co-primary outcomes were 12-month change in BMI and fasting insulin.

Results

There were no significant differences by randomization for either primary outcome at 12 months. Among youth who completed 6-month assessments before the COVID-19 pandemic, the TTP intervention, compared to the control arm, was associated with significantly decreased change values for age/sex-adjusted BMI z-scores (p = 0.028) and waist circumference (p = 0.040) at 6 months.

Conclusions

In this trial among American Indian youth spanning the COVID-19 pandemic, the TTP intervention yielded short-term improvements on obesity measures but only in the subset who participated before the pandemic.

Background

A dual-energy x-ray absorptiometry (DXA)-derived phenotype classification based on fat mass and muscle mass has been developed for adults. We extended this to a paediatric population.

Methods

Children's (≤ 17 years) DXA data in NHANES (n = 6120) were used to generate sex- and age-specific deciles of appendicular skeletal muscle mass index and fat mass index with the Lambda Mu Sigma method. Four phenotypes (high [H] or low [L], adiposity [A] and muscle mass [M]: HA-HM, HA-LM, LA-HM, LA-LM) were identified based on being above/below the median compared to same-sex and same-age peers. These reference curves were applied to the QUALITY cohort (n = 630, 8–10 years of age in 2005) to assess whether the phenotypes correctly identified cardiometabolic risk at baseline, follow-up (2008–2010), and their longitudinal changes. Multiple linear regression models were adjusted for age, sex, and Tanner's stage.

Results

Compared to the LA-HM reference group, the HA-HM phenotype was associated with less favourable HDL, triglycerides, and HOMA-IR at baseline and first follow-up, but not in their changes. The HA-LM phenotype was associated with less favourable HOMA-IR at baseline and first follow-up.

Conclusions

Results suggest that phenotypes based on fat and muscle mass may have clinical utility in children and should be further investigated.

Background

How reduced sleep impacts screen time in children is unclear.

Objectives

To explore how reduced sleep impacts objectively measured screen use.

Methods

One hundred and five children (8–12 years) with caregiver-reported sleep of 8–11 h/night were randomised to 7 nights sleep extension (go to bed 1 h earlier) or sleep restriction (bed 1 h later) in a crossover trial with a 7-night washout between conditions. Sleep and time awake were measured using waist-worn accelerometry (ActiGraph wGT3X-BT) and screen time using wearable cameras (Brinno TLC130 Timelapse) and questionnaires. Camera images were coded as time spent on screens (raw data), including imputation for blocked images (Rules 1 and 2). Within-person differences (95% CI) were calculated in those with matched camera data across sleep intervention weeks, in minutes and as percentage of awake time.

Results

Screen time before school or on weekends did not differ in the 49 children (10.4 years, 51% female, 41% overweight, 78% European) with suitable camera data. After school, children appeared to have similar screen time using raw data (median difference; 25th, 75th percentiles: 18.7 min; −10.2, 72.5), but greater screen time during sleep restriction compared with extension after allowance for blocked images (Rule 2: 66.3 min; 7.5, 102.9 or 6% of awake time; 0.5, 10.0). Parents (n = 98) reported greater total screen use in children during the sleep restriction week (mean difference; 95% CI: 16.8 min; 1.8, 31.8).

Conclusions

In this secondary analysis, getting less sleep appeared to increase screen time in children during the weekday afternoon and evening hours, compared to when they received more sleep.

Trial Registration: ACTRN12618001671257 Australian New Zealand Clinical Trials Registry; ANZCTR.

Background

Childhood obesity interventions often overlook sleep and emotional wellbeing, though research shows both are associated with weight status across childhood. The timing of their co-development and the most effective point for intervention remain poorly understood. The aim of this study was to examine the trajectories of sleep, weight status and emotional wellbeing using the Growing Up in Scotland birth cohort 1 dataset.

Methods

This study conducted secondary data analyses from sweeps 1–10 (10 months-14 years). Sleep was assessed through main-carer and self-reports, covering duration, bedtime, fragmentation, insomnia symptoms and oversleeping. Weight status was evaluated using BMI percentiles from objective height and weight measurements. Emotional wellbeing was evaluated using the emotional symptoms subscale of the Strengths and Difficulties Questionnaire. Trajectories were categorised as stable, improving, or declining for wellbeing; stable, obesogenic or leptogenic for weight; and compared against age-specific recommendations for sleep.

Results

Analyses from 4157 participants (50.2% male) showed that sleep duration declined with age, falling significantly below age-specific recommendations between 8 and 14 years. Bedtimes became later and more variable between 8 and 10 years, with insomnia symptoms and delayed sleep onset common by age 14. Obesogenic or fluctuating weight trajectories were observed in 51.2% of participants. Emotional wellbeing declined notably between 10 and 14 years.

Conclusions

Declines in sleep and emotional wellbeing coincided with rising obesity rates between ages 10 and 12. Targeted intervention between ages 8 and 10 years offers a critical opportunity to mitigate risks of obesity, poor sleep and declining emotional wellbeing before adolescence.

Background

While the clinical signs of cardiovascular diseases (CVDs) are not usually visible until adulthood, the CVD pathology begins already in childhood.

Objectives

To study the associations of physical activity (PA) and dietary fat quality with arterial health among adolescents.

Methods

Altogether 117 adolescents 15–17 years of age participated in the study. Sedentary time (ST), light PA, moderate-to-vigorous PA (MVPA), PA energy expenditure (PAEE), resistance training volume and dietary fat quality were assessed. Pulse wave velocity (PWV) and cardio-ankle vascular index (CAVI) were assessed by impedance cardiography, and carotid artery intima-media thickness (cIMT) and carotid artery distensibility were assessed by carotid ultrasonography.

Results

ST was negatively associated with cIMT (standardised regression coefficient β = −0.225, p = 0.015). MVPA and PAEE were negatively associated with PWV (β = −0.245 to −0.228, p < 0.05) and CAVI (β = −0.226 to −0.212, p < 0.05), and positively with cIMT (β = 0.235 to 0.269, p < 0.05). MVPA was positively associated with carotid artery distensibility (β = 0.180, p = 0.047). Monounsaturated fat intake was positively associated with carotid artery distensibility (β = 0.190, p = 0.041). PAEE was negatively associated with CAVI in adolescents with higher saturated fat (SFA) intake (β = −0.367, p = 0.017), but not in adolescents with lower SFA intake (β = −0.095, p = 0.526).

Conclusion

MVPA and PAEE were related to better arterial health. Moreover, our results suggest that higher PAEE benefits adolescents with higher SFA intake.

Objective

Lifestyle intervention is a cost-effective approach for preventing type 2 diabetes among adults with prediabetes. The purpose of this study was to examine the cost and incremental cost-effectiveness ratio (ICER) of an intensive lifestyle intervention compared with usual care among youth with prediabetes.

Methods

Latino youth ages 12–16 years with obesity and prediabetes were randomised to a 6-month lifestyle intervention (INT, N = 79) or usual care (UC, N = 38). Between-group difference in change in 2-h post-challenge glucose was non-significant at 6 months (7.2 mg/dL; 95% CI, −5.3, 19.7) and 12 months (0.3 mg/dL; 95% CI, −14.1, 14.5). Cost and ICERs were calculated from health care, family and total societal (health care plus family) perspectives in 2019 US Dollars. The study was conducted from May 2016 to March 2020.

Results

The estimated societal cost per participant was $1935.21 (95% CI, $1583.12, $2315.05) for the INT and $234.20 ($190.71, $278.61) for the UC during the first 6 months. During the entire 12 months of the trial, the societal cost per participant increased to $468.40 ($379.19, $568.37) for the UC, but there were no additional costs for the INT. The ICER for 2-h glucose for the INT compared with the UC was $222.78 and $4816.57 per mg/dL at 6 and 12 months.

Conclusions

Among Latino youth with prediabetes, an intensive lifestyle intervention resulted in a nonsignificant reduction in 2-h glucose at a higher cost compared with usual care.

Background

The National Health and Nutrition Examination Survey provides nationally representative data on child obesity using measured height and weight. Due to COVID-19, the NHANES August 2021–August 2023 cycle had design changes and smaller sample sizes for certain race/Hispanic origin groups. The objective is to explore sex and race/Hispanic origin-specific childhood obesity trends.

Methods

Trends from 1999 or 2007 to August 2023 were evaluated in regression models. Obesity was defined as BMI-for-age ≥ 95th percentile.

Results

Analyses included 28 666 youth 2–19 years. From 2007 to August 2023, obesity prevalence increased among Hispanic girls (p = 0.03) but not Hispanic boys (p = 0.06). From 1999 to August 2023, obesity increased among non-Hispanic White (White) boys (p = 0.02) and non-Hispanic Black (Black) girls (p = 0.04), but not White girls (p = 0.10). Among Black boys only, a quadratic trend (p = 0.03) was found, driven by an obesity increase between 2017–2018 and August 2021–August 2023, from 19.4% to 38.1% (p < 0.01).

Conclusions

Obesity increased among Hispanic girls, White boys, and Black girls. The prevalence increased in Black boys too, but the magnitude of increase from 2017 to August 2023 appears implausible. Small August 2021–August 2023 sample sizes for Black youth could have exacerbated unmeasured sampling variation. Continued surveillance will provide context for interpreting estimates.