Childhood Obesity最新文献

Background: Although numerous studies have reported that obesity in adolescents is related to shorter sleep duration, few studies have reported the effect of sleep timing, particularly early wake-up time, on obesity. Objectives: To investigate the association between wake-up time and adolescent obesity. Methods: Using the Korean National Health and Nutrition Examination Survey VII data, 1301 middle school and high school students were selected and grouped according to BMI. Sleep timing and lifestyle factors were evaluated using self-reported questionnaires. Results: The mean bedtime and wake-up time were 00:09 am and 07:06 am, respectively. Despite similar bedtimes, the group with overweight/obesity woke up earlier than the group with underweight/normal weight. The BMI z-score and the overweight/obesity relative risk decreased as the wake-up time was delayed, even after adjustment for covariates. Participants who woke up before 06:50 am had a 1.82-fold higher risk of having overweight/obesity than those who woke up after 07:30 am. Participants who woke up late tended to sleep longer than those who woke up early. Conclusions: Waking up early is significantly associated with an increased BMI z-score in adolescents and may be a risk factor for overweight/obesity.

Objective: To describe satisfaction with the telehealth aspect of a pediatric obesity intervention among families from multiple rural communities and assess differences in satisfaction based on sociodemographic factors. Methods: This is a secondary analysis of data from a pilot randomized controlled trial of a 6-month intensive lifestyle intervention (iAmHealthy) delivered through telehealth to children 6-11 years old with BMI ≥85th%ile and their parents from rural communities. Parents completed a sociodemographic survey and a validated survey to assess satisfaction with the telehealth intervention across four domains (technical functioning, comfort of patient and provider with technology and perceived privacy, timely and geographic access to care, and global satisfaction) on a 5-point Likert scale. Kruskal-Wallis nonparametric rank test were used to compare mean satisfaction scores based on parent sociodemographics. Results: Forty-two out of 52 parents (67% White, 29% Black, 5% multiracial, and 50% with household income <$40,000) completed the survey. Mean satisfaction scores ranged from 4.16 to 4.54 (standard deviation 0.44-0.61). Parents without a college degree reported higher satisfaction across all domains compared with parents with a college degree, including global satisfaction (mean 4.64 vs. 4.31, p = 0.03). Parents reporting a household income <$40,000 (mean 4.70) reported higher scores in the comfort with technology and perceived privacy domain compared with parents with higher incomes (mean 4.30-4.45, p = 0.04). Discussion: Parents from rural communities, especially those from lower socioeconomic backgrounds, were highly satisfied with the iAmHealthy telehealth intervention. These findings can be used to inform future telehealth interventions among larger more diverse populations. ClinicalTrials.gov Identifier: NCT04142034.

Background: Dietary patterns during pregnancy may contribute to gestational weight gain (GWG) and birthweight, but there is limited research studying these associations in racial and ethnic minority groups. The objective of this study was to evaluate associations between prenatal dietary patterns and measures of GWG and birthweight in a cohort of culturally diverse Hispanic women with low incomes. Methods: Data were analyzed from 500 mother-infant dyads enrolled in the Starting Early Program, a childhood obesity prevention trial. Diet over the previous year was assessed in the third trimester of pregnancy using an interviewer-administered food frequency questionnaire. Dietary patterns were constructed using the Healthy Eating Index-2015 (HEI-2015) and principal components analysis (PCA) and analyzed as tertiles. GWG and birthweight outcomes were abstracted from medical records. Associations between dietary pattern tertiles and outcomes were assessed by multivariable linear and multinomial logistic regression analyses. Results: Dietary patterns were not associated with measures of GWG or adequacy for gestational age. Greater adherence to the HEI-2015 and a PCA-derived dietary pattern characterized by nutrient-dense foods were associated with higher birthweight z-scores [β: 0.2; 95% confidence interval (CI): 0.04 to 0.4 and β: 0.3; 95% CI: 0.1 to 0.5, respectively], but in sex-specific analyses, these associations were only evident in male infants (β: 0.4; 95% CI: 0.03 to 0.7 and β: 0.3; 95% CI: 0.03 to 0.6, respectively). Conclusions: Among a cohort of culturally diverse Hispanic women, adherence to healthy dietary patterns during pregnancy was modestly positively associated with increased birthweight, with sex-specific associations evident only in male infants.

Background: Drivers of summer body mass index (BMI) gain in children remain unclear. The Circadian and Circannual Rhythm Model (CCRM) posits summer BMI gain is biologically driven, while the Structured Days Hypothesis (SDH) proposes it is driven by reduced structure. Objectives: Identify the mechanisms driving children's seasonal BMI gain through the CCRM and SDH. Methods: Children's (N = 147, mean age = 8.2 years) height and weight were measured monthly during the school year, and once in summer (July-August). BMI z-score (zBMI) was calculated using CDC growth charts. Behaviors were measured once per season. Mixed methods regression estimated monthly percent change in children's height (%HΔ), weight (%WΔ), and monthly zBMI for school year vs. summer vacation, seasonally, and during school months with no breaks vs. school months with a break ≥1 week. Results: School year vs. summer vacation analyses showed accelerations in children's %WΔ (Δ = 0.9, Standard Error (SE) = 0.1 vs. Δ = 1.4, SE = 0.1) and zBMI (Δ = -0.01, SE = 0.01 vs. Δ = 0.04, SE = 0.3) during summer vacation, but %HΔ remained relatively constant during summer vacation compared with school (Δ = 0.3, SE = 0.0 vs. Δ = 0.4, SE = 0.1). Seasonal analyses showed summer had the greatest %WΔ (Δ = 1.8, SE = 0.4) and zBMI change (Δ = 0.05, SE = 0.03) while %HΔ was relatively constant across seasons. Compared with school months without a break, months with a break showed higher %WΔ (Δ = 0.7, SE = 0.1 vs. Δ = 1.6, SE = 0.2) and zBMI change (Δ = -0.03, SE = 0.01 vs. Δ = 0.04, SE = 0.01), but %HΔ was constant (Δ = 0.4, SE = 0.0 vs. Δ = 0.3, SE = 0.1). Fluctuations in sleep timing and screen time may explain these changes. Conclusions: Evidence for both the CCRM and SDH was identified but the SDH may more fully explain BMI gain. Interventions targeting consistent sleep and reduced screen time during breaks from school may be warranted no matter the season.

Background: Nonresponsive feeding styles can contribute to rapid weight gain in infancy and subsequent obesity in childhood. There is a need to investigate factors such as parental mental health symptoms (stress, depression, and anxiety) that may contribute to nonresponsive feeding styles. The purpose of this study was to investigate the relationship between parental mental health symptoms and feeding styles in parents of healthy, term formula-fed infants during the first year of life. Methods: A cross-sectional, descriptive correlational design was employed using online surveys. We recruited participants through Facebook groups and pediatricians' offices. Instruments included a demographic questionnaire, the Perceived Stress Scale-10, Patient Health Questionnaire-Depression Module-9, 7-item Generalized Anxiety Disorder Assessment, and Infant Feeding Style Questionnaire. Results: Participants were 306 parents of formula-fed infants. Greater depressive symptoms was the strongest predictor of the pressuring style (β = 0.54), while greater symptoms of stress (β = -0.13) and anxiety (β = -0.28) were associated with lower pressuring scores. Greater depressive symptoms was the strongest predictor of the laissez-faire style (β = 0.48), while greater symptoms of stress (β = -0.17) and anxiety (β = -0.23) were associated with lower laissez-faire scores. Engaging in ≤50% of the infant's feeds was the strongest control variable predictor for the pressuring and laissez-faire styles. None of the mental health variables were significantly related to the restrictive style. Conclusions: We recommend increased screening for depressive symptoms in parents of infants and responsive feeding support, especially for those experiencing depressive symptoms.

Background: Early childhood weight trajectory is associated with future risk for obesity. However, little is known about the association of birth weight and weight trajectories before age 5.5 years with severe adult obesity. Methods: This study used a nested case-control design of 785 matched sets of cases and controls matched 1:1 on age and gender from a 1976 to 1982 birth cohort in Olmsted County, Minnesota. Cases with severe adult obesity were defined as individuals with a BMI ≥40 kg/m² after 18 years of age. There were 737 matched sets of cases and controls for the trajectory analysis. Weight and height data from birth through 5.5 years were abstracted from the medical records, and weight-for-age percentiles were obtained from the CDC growth charts. Results: A two-cluster weight-for-age trajectory solution was identified as optimal, with cluster 1 having higher weight-for-age before age 5.5 years. While there was no association between birth weight and severe adult obesity, the odds of being in cluster 1, which includes children with higher weight-for-age percentiles, was significantly increased for cases compared with controls [odds ratio (OR) 1.99, 95% confidence interval (CI) 1.60-2.47]. The association between cluster membership and case-control status persisted after adjusting for maternal age and education (adjusted OR 2.08, 95% CI 1.66-2.61). Conclusions: Our data suggest that early childhood weight-for-age trajectories are associated with severe obesity status in adult life. Our results add to growing evidence that it is critical to prevent excess early childhood weight gain.

Background: Current treatment protocols to prevent and treat pediatric obesity focus on prescriptive lifestyle interventions. However, treatment outcomes are modest due to poor adherence and heterogeneity in responses. Wearable technologies offer a unique solution as they provide real-time biofeedback that could improve adherence to and sustainability of lifestyle interventions. To date, all reviews on wearable devices in pediatric obesity cohorts have only explored biofeedback from physical activity trackers. Hence, we conducted a scoping review to (1) catalog other biofeedback wearable devices available in this cohort, (2) document various metrics collected from these devices, and (3) assess safety and adherence to these devices. Methods: This scoping review was conducted adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. Fifteen eligible studies examined the use of biofeedback wearable devices beyond activity trackers in pediatric cohorts, with an emphasis on feasibility of these devices. Results: Included studies varied in sample sizes (15-203) and in ages 6-21 years. Wearable devices are being used to capture various metrics of multicomponent weight loss interventions to provide more insights about glycemic variability, cardiometabolic function, sleep, nutrition, and body fat percentage. High safety and adherence rates were reported among these devices. Conclusions: Available evidence suggests that wearable devices have several applications aside from activity tracking, which could modify health behaviors through real-time biofeedback. Overall, these devices appear to be safe and feasible so as to be employed in various settings in the pediatric age group to prevent and treat obesity.

This study was performed to explore the association between attention-deficit/hyperactivity disorder (ADHD) and the risk of overweight/obesity in both children and adolescents. The PubMed, Web of Science, and Cochrane Library databases were searched for relevant studies published before July 12, 2022. Studies with data for calculating the odds ratio (OR) of childhood overweight/obesity and ADHD were included. The literature value was assessed by the cross-sectional evaluation criteria proposed by the Agency for Healthcare Research and Quality (AHRQ). All analyses were conducted using StataSE 11 and RevMan 5.3 software with random-effects models. This review included a total of 16 studies covering 14,981 cases and 128,916 controls.According to the meta-analysis, children with ADHD had a significant risk for co-occurring overweight and obesity [OR 1.56; 95% confidence intervals (CI) 1.32-1.85], especially boys (OR 1.45; 95% CI 1.10-1.90), people in Asia (OR 3.25; 95% CI 1.70-6.21) and Europe (OR 1.85; 95% CI 1.61-2.12), and patients not using medication (OR 1.54; 95% CI 1.22-1.94).ADHD has a significant association with overweight and obesity in both children and adolescents, which may be altered by factors such as geography, gender, and medication use. Timely treatment should be provided to children and adolescents diagnosed with ADHD to inhibit the emergence of overweight and obesity.

Background: Challenges to treat excess weight in primary care settings include time constraints during encounters and barriers to multiple visits for patient families, especially those from vulnerable backgrounds. Dynamo Kids! (DK), a bilingual (English/Spanish) e-health intervention, was created to address these system-level challenges. This pilot study assessed the effect of DK use on parent-reported healthy habits and child BMI. Methods: In this 3-month, quasi-experimental cohort design, DK was offered to parents with children aged 6-12 years with BMI ≥85th percentile in three public primary care sites in Dallas, Texas. DK included three educational modules, one tracking tool, recipes, and links to internet resources. Parents completed an online survey before and after 3 months. Pre-post changes in family nutrition and physical activity (FNPA) scores, clinic-measured child %BMI_p95, and self-reported parent BMI were assessed using mixed-effects linear regression modeling. Results: A total of 73 families (mean child age = 9.3 years; 87% Hispanic, 12% non-Hispanic Black, and 77% Spanish-speaking families) completed the baseline survey (participants) and 46 (63%) used the DK site (users). Among users, pre-post changes (mean [standard deviation]) showed an increase in FNPA scores (3.0 [6.3], p = 0.01); decrease in child %BMI_p95 (-1.03% [5.79], p = 0.22); and decrease in parent BMI (-0.69 [1.76], p = 0.04). Adjusted models showed -0.02% [95% confidence interval: -0.03 to -0.01] change in child %BMI_p95 for each minute spent on the DK website. Conclusions: DK demonstrated a significant increase in parent FNPA scores and decrease in self-reported parent BMI. e-Health interventions may overcome barriers and require a lower dosage than in-person interventions.