Childhood Obesity最新文献

Background: The purpose of this study was to determine how accurately parents measure their preschool child's weight and height with increasing levels of instruction. Methods: Parents measured their child's (n = 30 dyads) weight (own weight scale) and height (soft tape measure) using three levels of instruction: instructional guide (level 1); guide, demonstration video (level 2); and guide, video, and virtual monitoring (level 3), which were compared to researcher measurements (electronic weight scale, Stadiometer). Paired t-tests were used to determine differences between researcher and parent measurements and between the three parent levels. Inaccurate classifications were calculated using parent-measured values for the four categories (underweight, healthy, overweight, obese). Results: Raw mean parent-measured weights (17.4 ± 2.3 kg) differed from researcher by 0.2 kg (level 1), 0.3 kg (level 2), and 0.1 kg (level 3). Raw mean parent-measured heights (104.0 ± 5.9 cm) differed from researcher by 0.9 cm (level 1, p = 0.005), 0.4 cm (level 2, NS), and 0.3 cm (level 3, NS). Across all levels, 48.9% and 65.5% parents overmeasured their children's weights and heights, respectively. Using parent-measured values, 29.4% of children were classified high while 70.5% were classified low. Parents were more likely to make errors if their children were on the borderline between any of the two weight categories. Conclusion: Findings indicate that an instructional guide with demonstration video is helpful in improving the parents' accuracy of their children's weights and heights. More research is needed to determine accuracy in population other than White parents with high education levels and children under overweight and obese category.

Background: Family is an important determinant of youth's health behaviors, yet research on the importance of intragenerational relationships for determining physical activity (PA) and sedentary behaviors (SBs) is limited. This study examined correlations in siblings' total PA, moderate-to-vigorous physical activity (MVPA), and SB and explored potential determinants of differences in Hispanic/Latino siblings' activity. Methods: Hispanic/Latino 8-16-year olds from the cross-sectional Hispanic Community Children's Health Study/Study of Latino Youth with ≥1 sibling enrolled were examined (n = 535). Activity was assessed using the Actical accelerometer. Linear mixed models were used with total PA, MVPA, or SB as the outcome; correlations among siblings' PA and SB were assessed with intraclass correlation coefficients (ICCs). Results: ICCs for siblings' total PA, MVPA, and SB were 0.26 (95% confidence interval: 0.16-0.36), 0.29 (0.21-0.38), and 0.42 (0.34-0.51), respectively. There were no differences in correlations between siblings who were all brothers compared to all sisters. However, compared to siblings of differing sexes, siblings who were all brothers had the strongest correlations in total PA (0.61 [0.46-0.76]) and MVPA (0.64 [0.49-0.78]), and siblings who were all sisters had the weakest correlations in SB (0.14 [-0.10 to 0.37]). Correlations did not differ according to age, and social and environmental measures did not explain differences in siblings' PA or SB. Conclusions: Correlations in Hispanic/Latino siblings' PA and SB ranged from slight to fair, with siblings who were all brothers generally having the strongest correlations. Future research should examine determinants of sex-specific differences in siblings' PA and SB correlations.

Background: Sugar-sweetened beverage (SSB) and non-nutritive sweetened beverage (NNSB) consumption is associated with obesity and are targets for population-level dietary interventions. In children (<16 years), we evaluate whether SSB or NNSB consumption is associated with subsequent (2 years later) overweight and/or obesity, and the effect of consumption on subsequent overweight/obesity differs by BMI polygenic risk score (BMI-PRS). Methods: The nationally representative Longitudinal-Study-of-Australian-Children had biennial data collection from birth (n = 5107) until age 14/15 years (n = 3127). At age 11/12 years, a comprehensive biomedical assessment, including PRS assessment, was undertaken (n = 1422). Parent- or self-reported beverage consumption (SSBs: soft drinks, energy drinks, and/or juice; NNSBs: diet drinks) was measured as any/none over previous 24 hours. BMI-PRS was derived using published results (high PRS ≥75th percentile). At ages 4/5-14/15 children were classified as having obesity, overweight/obesity, or not having overweight/obesity using BMI z-score (CDC cut points). Results: SSB consumption had limited association with subsequent overweight/obesity. NNSB consumption was associated with ∼8% more children with subsequent overweight/obesity at most ages. In older children with high BMI-PRS, associations between NNSB consumption and subsequent overweight/obesity strengthened with age [at age 14-15 for high BMI-PRS, difference in proportion with overweight/obesity among NNSB consumers vs. nonconsumers = 0.38 (95% confidence interval: 0.22 to 0.55, p ≤ 0.001)]. There was limited association between SSB consumption and BMI-PRS. Conclusion: NNSB consumption was associated with increased risk of overweight/obesity for children with greater genetic risk at older ages (12-15 years). Focused intervention among children with high genetic risk could target NNSB consumption; however, reverse causality (children with genetic risk and/or high BMI consume more NNSBs) cannot be excluded.

The COVID-19 pandemic has been associated with increases in pediatric obesity and widening pre-existing disparities. To better understand the pandemic's long-term impacts, we evaluated trends in obesity across different demographic groups during the pandemic through December 2022. Using a retrospective cohort design, we analyzed electronic health record data from a large pediatric primary care network. Logistic regression models fit using generalized estimating equations estimated odds ratios (ORs) for changes in the level and trajectory of obesity across 2-year month-matched periods: prepandemic (June 2017 to December 2019) and pandemic (June 2020 to December 2022). Among a cohort of 153,667 patients with visits in each period, there was a significant increase in the level of obesity at the pandemic onset [OR: 1.229, 95% confidence interval (CI): 1.211-1.247] followed by a significant decrease in the trend for obesity (OR: 0.993, 95% CI: 0.992-0.993). By December 2022, obesity had returned to prepandemic levels. However, persistent sociodemographic disparities remain.

Background: Prior investigators have examined the relationship between neighborhood public transportation access and physical activity among adolescents, but research is lacking on the association with obesity in this age group. This study examines the association between neighborhood public transportation access and adolescent BMI using a national sample. Methods: We used cross-sectional data from the Family Life, Activity, Sun, Health, and Eating study, a national survey (2014) that assessed physical activity and diet, among adolescents (aged 12-17 years, N = 1737) and their parents. We ran crude and adjusted linear regression models to test the association between neighborhood-level public transportation access (less prevalent and prevalent) and individual participant-level BMI z-scores. Results: The analytic sample included 336 adolescents (50% female; 69% had healthy weight; 28% had overweight or obesity). Adjusted models showed a positive relationship between high public transportation access and adolescent z-BMI (b = 0.25, confidence interval [95% CI]: -0.01 to 0.50). In stratified analyses, high public transportation access was associated with higher z-BMI for high school students (b = 0.57, 95% CI: 0.23-0.91), males (b = 0.48, 95% CI: 0.09-0.87), and adolescents in households with an income below $99,999 (0.29, 95% CI: 0.02-0.56). Conclusion: Neighborhood public transportation access is associated with adolescent BMI, but the direction of this association varies across urban adolescent demographic subgroups. Further research is needed to clarify the relationships between individual and social-environmental factors that impact public transportation access and its association with adolescent BMI.

Obesity care in pediatric populations has entered a new era. The recent discovery of molecular genetic causes for abnormal weight gain, development of antiobesity medications, mounting data on the robust efficacy and favorable safety profile of bariatric surgery, and implementation of clinical guidelines fill a long-standing gap in the care of children affected by obesity, one of the most challenging pediatric diseases. However, these novel clinical approaches do not appear to have reached every individual who is in need, particularly children with chronic health conditions (CHCs), raising important questions for equitable medical care. In this study, we discuss specific etiologies, challenges, and ideas for future directions in diagnosing and managing obesity in children with CHCs. Although this article is not intended to be utilized as clinical guidelines, it underscores potential practical solutions for the current issues.

Background: Fewer than 1/4th of US children and adolescents meet physical activity (PA) guidelines, leading to health disparities that track into adulthood. Neighborhood opportunity may serve as a critical modifiable factor to improve fitness attainment and reduce these disparities. We drew data from the Child Opportunity Index to examine associations between neighborhood indicators of opportunity for PA and multiple fitness indicators among New York City public school youth. Methods: Multilevel generalized linear mixed models were used to estimate the overall and sex-stratified associations between neighborhood indicators (green space, healthy food, walkability, commute time) and indicators for physical fitness [curl-ups, push-ups, Progressive Aerobic Cardiovascular Endurance Run (PACER), sit-and-reach] using the New York City FITNESSGRAM data set. Results: The analytic sample [n = 299,839; median (interquartile range) age = 16 (12-17)] was 50.1% female, 37.5% Hispanic, 26.2% non-Hispanic Black, and most (69.5%) qualified for free/reduced price school meals. Neighborhood indicators were positively associated with higher values of indicators for physical fitness. The strongest associations were observed between walkability and both BMI and PACER, and commute time with BMI, push-ups, and PACER. For example, walkability had the greatest magnitude of effects for BMI and muscular strength and endurance (BMI: β: -0.75, 95% confidence interval, CI: -1.01 to -0.49; PACER: β: 1.98, 95% CI: 1.59 to 2.37), and particularly for girls compared with boys (BMI, girls: β: -0.91, 95% CI: -1.22 to -0.66); BMI, boys: β: -0.56, 95% CI: -0.86 to -0.25); PACER, girls: β: 2.11, 95% CI: 1.68 to 2.54; push-ups, boys: β: 1.71, 95% CI: 1.31 to 2.12). Conclusion: Neighborhood indicators were associated with multiple measures of youth fitness. Continued research on neighborhood opportunity and youth fitness may better inform place-based public health interventions to reduce disparities.

Background: This study aimed to assess the implementation and access to telehealth-delivered pediatric weight management (PWM) during the initial phase of the COVID-19 pandemic at six US PWM programs (PWMP) using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework. Methods: The COVID-19 period (COVID) was defined in this retrospective, multisite study as the time when each site closed in-person care during 2020. The Pre-COVID period (Pre-COVID) was an equivalent time frame in 2019. Patients were stratified by visit completion status. Patient characteristics for COVID and Pre-COVID were compared to examine potential changes/disparities in access to care. Results: There were 3297 unique patients included across the six sites. On average, telehealth was initiated 4 days after in-person clinic closure. Compared with Pre-COVID, COVID (mean duration: 9 weeks) yielded fewer total completed visits (1300 vs. 2157) and decreased revenue (mean proportion of nonreimbursed visits 33.30% vs. 16.67%). Among the completed visits, COVID included a lower proportion of new visits and fewer patients who were male, non-English speaking, Hispanic, or Asian and more patients who were Black or lived ≥20 miles from the program site (p < 0.05 for all). Among no-show/canceled visits, COVID included more patients who had private insurance, older age, or a longer time since the last follow-up. Conclusion: Rapid implementation of telehealth during COVID facilitated continuity of PWM care. Clinic volume and reimbursement were lower during COVID and differences in the patient population reached by telehealth emerged. Further characterization of barriers to telehealth for PWM is needed.

Objective: The aim of this study was to examine associations of childhood physical activity, sedentary behavior, and dietary intake with adiposity trajectories from childhood to adolescence. Methods: Quebec Adipose and Lifestyle Investigation in Youth (QUALITY) cohort (n = 630) data from 3 time points (8-10, 10-12, and 15-17 years) for 377 Caucasian children with parental obesity were analyzed. Height and weight, physical activity and sedentary behavior (7-day accelerometry), screen time (self-reported), and dietary intake (three 24-hour diet recalls) were measured. Group-based trajectory modeling identified longitudinal trajectories of body-mass index z-scores (zBMIs). Inverse probability of exposure-weighted multinomial logistic regressions examined associations between baseline lifestyles and zBMI trajectory groups. Results: Six trajectory groups were identified: Stable-Low-Normal-Weight (two groups, 5.7% and 33.0%, which were combined), Stable-High-Normal-Weight (24.8%), Stable-Overweight (19.8%), Stable-Obesity (8.8%), and Overweight-Decreasers (7.9%). For every additional portion of fruits and vegetables, the likelihood of being in the group of Overweight-Decreasers increased by 29% (odds ratio [OR]: 1.29, 95% confidence interval [CI]: 1.09-1.55) compared with the reference group (Stable-Low-Normal-Weight). For every additional hour of sedentary behavior, the likelihood of belonging to the group of Overweight-Decreasers increased 2-fold (OR: 1.99, 95% CI: 1.28-3.21) and Stable-Obesity increased 1.5-fold (OR: 1.56, 95% CI: 1.08-2.23), compared with the reference. Every additional 10 minutes of moderate-to-vigorous physical activity was associated with a lower likelihood of belonging to the Stable-Obesity group (OR: 0.75, 95% CI: 0.61-0.89) and to the group of Overweight-Decreasers (OR: 0.79, 95% CI: 0.64-0.95) compared with the reference. Finally, children were more likely to belong to the Stable-Obesity group with each additional hour/day of screen time (OR: 1.23, 95% CI: 1.01-1.58). Conclusions: Trajectories of zBMIs from childhood to late adolescence were stable, except for one group which decreased from overweight in childhood to normal weight in adolescence. The latter had more favorable baseline dietary intake of fruits and vegetables. ClinicalTrials.org no. NCT03356262.

Background: Understanding how different populations respond to a childhood obesity intervention could help optimize personalized treatment strategies, especially with the goal to reduce disparities in obesity. Methods: We conducted a secondary analysis of the Greenlight Cluster Randomized Controlled Trial, a health communication focused pediatric obesity prevention trial, to evaluate for heterogeneity of treatment effect (HTE) by child biological sex, caregiver BMI, caregiver reported race and ethnicity, primary language, and health literacy. To examine HTE on BMI z-score from 2 to 24 months of age, we fit linear mixed effects models. Results: We analyzed 802 caregiver-child pairs, of which 52% of children were female, 58% of households reported annual family income of <$20,000, and 83% did not have a college degree. We observed evidence to suggest HTE by primary language (p = 0.047 for Spanish vs. English) and the combination of primary language and health literacy (p = 0.01). There was insufficient evidence to suggest that the Greenlight intervention effect differed by biological sex, caregiver BMI, or by race/ethnicity. Conclusions: This HTE analysis found that the Greenlight obesity prevention intervention had a more beneficial effect on child BMI z-score over 2 years for children of caregivers with limited health literacy and for caregivers for whom Spanish was the primary language.