Childhood Obesity最新文献

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.

Background: Previous research has identified food insecurity as a risk factor for obesity but those studies employed cross-sectional designs and were largely focused on adults and young children. In addition, there is a paucity of studies examining the association between food insecurity and changes in children's overall diet quality. This study aimed to assess whether food insecurity is associated with subsequent changes in diet quality and BMI z-scores over 2 years among 7- to 12-year-old children. Methods: We used 2011-2019 secondary data (n = 404) from three randomized controlled trials in Minnesota. Food insecurity was identified using the U.S. Household Food Security Survey Module at baseline (Time 0). Diet quality was determined using the Healthy Eating Index (HEI)-2015 from 24-hour recalls, and BMI z-scores were calculated using measured height and weight. These two outcomes were measured at Time 0, Time 1 (10-12 months from Time 0), and Time 2 (15-24 months from Time 0). Results: Compared with children from food-secure households, those from food-insecure households experienced a 0.13 greater increase in BMI z-scores from Time 0 to Time 2 [95% confidence interval (CI): 0.04 to 0.21] and a 4.5 point increase in HEI-2015 from Time 0 to Time 1 (95% CI: 0.99 to 8.01). Conclusion: Household food insecurity may widen weight disparities among elementary school-aged children. Further studies are needed to identify the role of diet quality in weight changes among children with food insecurity. Clinical Trial Registration Number: NCT01538615, NCT02029976, NCT02973815.

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.

Background: To characterize the association between multiple social determinants of health (SDOH) and overweight and obesity among US children. Methods: We conducted a cross-sectional analysis using the 2016-2020 National Survey of Children's Health. SDOH domains consisted of Economic Stability, Social and Community Context, Neighborhood and Built Environment, and Health Care Access and Quality. We used ordinal logistic regression to model associations between SDOH and weight status and calculate predicted probabilities of having overweight or obesity for various SDOH profiles. Results: Data from 81,716 children represented a weighted sample of 29,415,016 children ages 10-17 years in the United States. Of these, 17% had overweight and 17% had obesity. Compared with children with the theoretically lowest-risk SDOH profile, children with the highest-risk SDOH profiles in all four domains had an odds ratio of having a higher BMI category of 4.38 (95% confidence interval 1.67-7.09). For the lowest risk profile, the predicted probability of obesity varied from 8% to 11%, depending on race. For the highest risk profile, the predicted probability of obesity varied from 26% to 34%, depending on race. Conclusions: While high-risk values in each SDOH domain were associated with higher predicted probability of overweight and obesity, it was the combination of highest risk values in all the SDOH domains that led to greatest increases. This suggests a complex and multilayered relationship between the SDOH and childhood obesity, necessitating a comprehensive approach to addressing health equity to reduce childhood obesity.

Childhood obesity is an ongoing concern in the United States. Higher weight status in early childhood is associated with higher weight status at older ages. The Maternal Obesity Matters (MOMs) Study investigated associations between maternal risk of cardiovascular disease (CVD) and child BMI z-scores (BMIz) among preschool-aged children. This cross-sectional exploratory study included mothers and their 3- to 5-year-old children in Colorado, United States. Maternal nonfasting blood samples, blood pressure, and maternal and child anthropometrics were collected. Maternal CVD risk was assessed on a scale of 0-5 using five health measures. Multivariate regression tested associations between maternal CVD risk and child BMIz. Each 1-point increase in maternal CVD risk was associated with a 0.18 increase in child BMIz, controlling for maternal employment. Intervening upon maternal health may be an important strategy for addressing childhood obesity.

Background: Youth with excess weight are at risk of developing type 2 diabetes (T2DM). Guidelines recommend screening for prediabetes and/or T2DM after 10 years of age or after puberty in youth with excess weight who have ≥1 risk factor(s) for T2DM. Electronic health records (EHRs) offer an opportunity to study the use of tests to detect diabetes in youth. Methods: We examined the frequency of (1) diabetes testing and (2) elevated test results among youth aged 10-19 years with at least one BMI measurement in an EHR from 2019 to 2021. We examined the presence of hemoglobin A1C (A1C), fasting plasma glucose (FPG), or oral glucose tolerance test (2-hour plasma glucose [2-hrPG]) results and, among those tested, the frequency of elevated values (A1C ≥6.5%, FPG ≥126 mg/dL, or 2-hrPG ≥200 mg/dL). Patients with pre-existing diabetes (n = 6793) were excluded. Results: Among 1,024,743 patients, 17% had overweight, 21% had obesity, including 8% with severe obesity. Among patients with excess weight, 10% had ≥1 glucose test result. Among those tested, elevated values were more common in patients with severe obesity (27%) and obesity (22%) than in those with healthy weight (8%), and among Black youth (30%) than White youth (13%). Among patients with excess weight, >80% of elevated values fell in the prediabetes range. Conclusions: In youth with excess weight, the use of laboratory tests for prediabetes and T2DM was infrequent. Among youth with test results, elevated FPG, 2hrPG, or A1C levels were most common in those with severe obesity and Black youth.