Childhood Obesity最新文献

Background: There are now four FDA-approved anti-obesity medications (AOMs) for youth ≥12 years, which can be effective therapies to treat obesity and obesity-related comorbidities. Objectives: This study describes parent/guardian (caregiver) openness to using AOMs for adolescents with obesity and evaluates factors that may contribute to openness. Methods: Caregivers of adolescents aged 12-17 years were surveyed. Self-reported height, weight, demographic information, family, and personal history of obesity or obesity-related comorbidities were collected. Participants rated their openness to starting an AOM for their child for obesity alone or obesity-related comorbidities on a 7-point Likert scale. A Likert rating of less than 4 was considered "less open" versus 4-7 was considered "more open." Results: A total of 344 participants completed the survey. Average openness toward AOM use for obesity as the only indication (as opposed to comorbid conditions) was 3.2 ± 1.74. Caregivers who were knowledgeable that the FDA-approved AOM use in adolescents had greater odds of being open to using these medications compared with caregivers who were not knowledgeable (odds ratio: 2.18; 95% confidence interval: 1.25-2.86). Conclusions: Caregivers reported openness to starting an AOM if they had prior knowledge of these medications, highlighting the need for family education on AOM use and indications.

Background: Amblyopia is the most common cause of vision loss in children. Amblyopia has been associated with impaired depth perception but little attention has been paid to the extent to which amblyopia increases the risk of obesity. Methods: Public-use data from the 1999-2008 National Health and Nutrition Examination Survey were used. Analyses were limited to children aged 12-18, who had a visual examination, and a best corrected visual acuity (BCVA) of at least 20/40 in the better-seeing eye. Amblyopia was defined as two or more-line interocular difference in BCVA. Obesity was defined as Body Mass Index (BMI) or body fat percentage (BFP) ≥95th percentile for age and gender. Sedentary lifestyle was defined as cardiovascular fitness level (CFL) rating of "low." We used Mantel-Haenszel odds ratios (ORs) to examine the relative prevalence of obesity in children with/without amblyopia. Results: Adolescents with amblyopia (n = 360) were more likely than those without (n = 7935) to have a high BMI [OR = 1.56; 95% confidence interval (CI): 1.24-1.98; p < 0.001]. The associations with either high BFP (OR = 1.20; 95% CI: 0.86-1.56, p = 0.167) or low CFL (OR = 1.15; 95% CI: 0.83-1.57; p = 0.267) were not statistically significant but in the direction of a priori hypotheses. Conclusions: This analysis of population-based data suggests that adolescents with amblyopia may be at higher risk of having obesity. Given the high prevalence of amblyopia and the range of morbidities associated with childhood obesity, targeted interventions to reduce the risk of obesity among children with amblyopia could be warranted.

Existing studies that have demonstrated a positive association between obesity and depression have been among adults, did not utilize the Patient Health Questionnaire (PHQ), or were conducted in a homogenous patient population. In this retrospective longitudinal cohort study of patients >11 and <18 years old with obesity in one health system we analyzed associations between change in BMI between two BMI measurements and PHQ-9 scores using chi-square and Kruskal-Wallis tests. We used PHQ-9 scores dichotomized at

Background: Promoting healthy eating and physical activity in early childhood education and care (ECEC) is recommended within guidelines and supported by health promotion programs; however, implementation is suboptimal. Evidence suggests implementation within the sector varies over time; however, this has not been empirically examined in relation to implementation barriers. This study aims to: (1) describe changes in the prevalence of, and barriers to, implementation of priority healthy eating and physical activity practices; and (2) explore the associations between such barriers and implementation. Methods: This was a repeated cross-sectional study over an 8-month period. A cross-section of 150-180 Australian ECEC services were prospectively randomly sampled for each month (April-November 2023), with 1127 ECEC services sampled in total and 20% of services sampled twice. Services reported via survey their implementation of two priority practices: (1) healthy menu standards and (2) educating and engaging parents in child physical activity. They also reported on implementation status, implementation stage, and five core implementation barriers. Results: Overall, 716 services completed 809 surveys. There were no significant differences in the prevalence of implementation or general trends in barriers to implementation of the two priority practices across that time. Services reporting less barriers were significantly more likely to be implementing the priority practices, and services in more advanced implementation stages were significantly less likely to report barriers. Conclusions: To enhance the implementation of priority practices in ECEC services, key barriers to implementation need to be understood and targeted to progress services through to advanced implementation stages.

Aim: Picky eating is a common appetitive trait reported among children and adolescents and may have detrimental effects on their weight, vegetable, and fruit intake, impacting health status. However, an updated systematic review of the literature and summary of effect estimates is required. This study aims to explore the association between picky eating with weight, vegetable and fruit intake, vegetable-only intake, and fruit-only intake. Methods: A systematic literature search of six electronic scientific databases and data extraction was performed between November 2022 and June 2023. Original articles that examined picky eating in association with weight, vegetable and/or fruit intake were included. PRISMA guidelines were followed and meta-analytical and meta-regression analyses were conducted to compute summary effect estimates and explore potential moderators. PROSPERO registration: CRD42022333043. Results: The systematic review included 59 studies of which 45 studies were included in the meta-analysis. Overall, the summarized effect estimates indicated that picky eating was inversely associated with weight [Cohen's d_z: -0.27, 95% confidence interval (CI): -0.41 to -0.14, p < 0.0001]; vegetable and fruit intakes (Cohen's d_z: -0.35, 95% CI: -0.45, -0.25, p < 0.0001); vegetable-only intake (Cohen's d_z: -0.41, 95% CI: -0.56, -0.26, p < 0.0001), and fruit-only intake (Cohen's d_z: -0.32, 95% CI: -0.45, -0.20, p < 0.0001). Picky eating was positively associated with underweight (Cohen's d_z: 0.46, 95% CI: 0.20, 0.71 p = 0.0008). Conclusion: Although effect sizes were small, picky eating was inversely associated with weight, vegetable, and fruit intakes, and positively associated with underweight in children and adolescents aged birth to 17 years.

Objective: (1) To describe the prevalence of high blood pressure (BP) and the association with BMI in young children with overweight/obesity; (2) to evaluate the accuracy of a single high BP to diagnose sustained hypertension over three visits. Methods: We used pre-intervention data from the Improving Pediatric Obesity Practice Using Prompts (iPOP-UP) trial. We included children aged 3-12 years with BMI ≥85th percentile at well-visits in 2019-2021 at 84 primary care practices in 3 US health systems in the Northeast, Midwest, and South. BP percentiles were calculated from the first visit with BP recorded during the study period. Hypertensive-range BP was defined by the 2017 American Academy of Pediatrics guideline. We tested the association between BMI classification and hypertensive BP using multivariable logistic regression. Results: Of 78,280 children with BMI ≥85th percentile, 76,214 (97%) had BP recorded during the study period (mean 7.4 years, 48% female, 53% with overweight, and 13% with severe obesity). The prevalence of elevated or hypertensive BP was 31%, including 27% in children with overweight and 33%, 39%, and 49% with class I, II, and III obesity, respectively. Higher obesity severity was associated with higher odds of hypertensive BP in the multivariable model. Stage 2 hypertensive BP at the initial visit had specificity of 99.1% (95% confidence interval 98.9-99.3) for detecting sustained hypertension over ≥3 visits. Conclusions: High BP is common in 3- to 12-year-olds with overweight/obesity, with higher obesity severity associated with greater hypertension. Children with overweight/obesity and stage 2 BP are likely to have sustained hypertension and should be prioritized for evaluation. Trial Registration: ClinicalTrials.gov Identifier: NCT05627011.

Background: Adolescent obesity rates continue to rise. A better understanding of who engages in emotional eating, a maladaptive eating style, is needed. Despite emotional eating being a frequent research target, the prevalence of emotional eating in US adolescents is currently unknown. Methods: Nationally representative adolescents (n = 1622, m = 14.48 years, 63.8% non-Hispanic White, 50.6% female) reported eating behaviors in the National Cancer Institute's Family Life, Activity, Sun, Health, and Eating (FLASHE) study. Frequencies and one-way ANOVAs were conducted to examine the rates of emotional eating across demographic and weight status groups. Correlations between emotional eating and dietary intake were examined. Results: In total, 30% of adolescents engaged in emotional eating. Older adolescents (35% of 17-year-olds), females (39%), non-Hispanic White individuals (32%), and adolescents with obesity (44%) had significantly higher rates of emotional eating. Controlling for weight status, greater adolescent emotional eating was correlated with more frequent intake of energy-dense/nutrient-poor foods (β = 0.10, p < 0.001), junk food (β = 0.12, p < 0.001), and convenience foods (β = 0.13, p < 0.001). Conclusions: This study fills a critical gap by providing insight into how common adolescent emotional eating is and highlighting demographic factors that are associated with higher rates. Nearly a third of adolescents in the United States reported eating due to anxiety or sadness, with rates higher in older adolescents, girls, non-Hispanic White adolescents, and adolescents with obesity. Emotional eating was associated with consuming less healthy foods, which conveys immediate and long-term health risks. Practitioners can intervene with emotional eating to reduce obesity and comorbid health risks.

Background: Research is needed to explore inequities in physical activity (PA) and access to healthy eating resources for children on a national scale. This study examined disparities in childhood obesogenic environments across all United States (US) counties by income and race/ethnicity and their interaction with county rurality. Methods: Data for four PA variables (exercise opportunities, school proximity, walkability, crime) and six nutrition variables (grocery stores, farmers markets, fast-food restaurants, full-service restaurants, convenience stores, and births at baby-friendly hospitals) were collected for all US counties (n = 3142) to comprise the Childhood Obesogenic Environment Index (COEI). Variables were ranked and allocated a percentile for each county, and a total obesogenic environment score was created by averaging variable percentiles. Analysis of variance was used to assess differences by tertiles of county-level median household income (low/intermediate/high) and percentage of non-Hispanic (NH) White residents (low/intermediate/high). Interaction tests were used to assess effect modification by rurality, and stratified results were presented for all significant interactions. Results: There were significant differences in COEI values according to tertiles of median household income (F = 260.9, p < 0.0001). Low-income counties (M = 54.3, SD = 8.3) had worse obesogenic environments than intermediate (M = 49.9, SD = 7.9) or high (M = 45.9, SD = 8.8) income counties. There was also a significant interaction between rurality and median household income (F = 13.9, p < 0.0001). Similarly, there were significant differences in COEI values according to tertiles of race/ethnicity (F = 34.5, p < 0.0001), with low percentage NH White counties (M = 51.8, SD = 9.8) having worse obesogenic environment scores than intermediate (M = 48.7, SD = 8.4) or high (M = 49.5, SD = 8.5) NH White counties. There was also a significant interaction between rurality and race/ethnicity (F = 13.9, p < 0.0001). Conclusion: Low-income counties and those with more racial/ethnic minority residents, especially in rural areas, had less supportive PA and healthy eating environments for youth. Targeted policy and environmental approaches that aimed to address concerns specific to underserved communities are needed.

Background: The etiology of obesity is multifaceted, with multiple risk factors occurring during early childhood (e.g., fast food frequency, eating dinner as a family, TV in the bedroom). Many past studies have largely considered obesity risk factors in isolation, when in reality, the risk factors likely cluster together. A latent class analysis can be used to identify patterns in child eating behaviors, parent feeding behaviors, and household habits among preschool-aged children and their families to identify distinct, heterogenous classes and to determine if classes are associated with overweight and obesity. Methods: We used data from a community-based study of 624 three- to five-year-old children and a parent in New Hampshire, from March 2014 to October 2015. Parent-reported data were used to determine frequency of eating behaviors and household habits. Height and weight were objectively measured. Results: Four classes were identified; Class 1: "Healthy/Mildly accommodating," Class 2: "Healthy/Accommodating," Class 3: "Moderately healthy/Moderately accommodating," and Class 4: "Least healthy/Least accommodating." Compared with Class 1, children in Class 4 had increased odds of being overweight or obese [adjusted odds ratio (aOR): 1.64, 95% confidence interval (CI): 1.13-2.15], whereas Classes 2 and 3 were not associated with BMI (Class 2: aOR: 1.24, 95% CI: 0.62-1.86; Class 3: aOR: 1.31, 95% CI: 0.81-1.81). Conclusion: Study findings highlight that child-parent interactions around meals differentially relate to children's weight status given the context of children's eating habits. Most important, our study findings confirm the importance of adapting multiple healthy habits within the home social and physical environment to offset obesity risk in young children.