Validity of the WHO cutoffs for biologically implausible values of weight, height, and BMI in children and adolescents in NHANES from 1999 through 2012

A better performing algorithm for identification of implausible growth data from longitudinal pediatric medical records

Tracking trajectories of body size in children provides insight into chronic disease risk. One measure of pediatric body size is body mass index (BMI), a function of height and weight. Errors in measuring height or weight may lead to incorrect assessment of BMI. Yet childhood measures of height and weight extracted from electronic medical records often include values which seem biologically implausible in the context of a growth trajectory. Removing biologically implausible values reduces noise in the data, and thus increases the ease of modeling associations between exposures and childhood BMI trajectories, or between childhood BMI trajectories and subsequent health conditions. We developed open-source algorithms (available on github) for detecting and removing biologically implausible values in pediatric trajectories of height and weight. A Monte Carlo simulation experiment compared the sensitivity, specificity and speed of our algorithms to three published algorithms. The comparator algorithms were selected because they used trajectory information, had open-source code, and had published verification studies. Simulation inputs were derived from longitudinal epidemiological cohorts. Our algorithms had higher specificity, with similar sensitivity and speed, when compared to the three published algorithms. The results suggest that our algorithms should be adopted for cleaning longitudinal pediatric growth data.

Power and reproducibility in the external validation of brain-phenotype predictions

Brain-phenotype predictive models seek to identify reproducible and generalizable brain-phenotype associations. External validation, or the evaluation of a model in external datasets, is the gold standard in evaluating the generalizability of models in neuroimaging. Unlike typical studies, external validation involves two sample sizes: the training and the external sample sizes. Thus, traditional power calculations may not be appropriate. Here we ran over 900 million resampling-based simulations in functional and structural connectivity data to investigate the relationship between training sample size, external sample size, phenotype effect size, theoretical power and simulated power. Our analysis included a wide range of datasets: the Healthy Brain Network, the Adolescent Brain Cognitive Development Study, the Human Connectome Project (Development and Young Adult), the Philadelphia Neurodevelopmental Cohort, the Queensland Twin Adolescent Brain Project, and the Chinese Human Connectome Project; and phenotypes: age, body mass index, matrix reasoning, working memory, attention problems, anxiety/depression symptoms and relational processing. High effect size predictions achieved adequate power with training and external sample sizes of a few hundred individuals, whereas low and medium effect size predictions required hundreds to thousands of training and external samples. In addition, most previous external validation studies used sample sizes prone to low power, and theoretical power curves should be adjusted for the training sample size. Furthermore, model performance in internal validation often informed subsequent external validation performance (Pearson's r difference <0.2), particularly for well-harmonized datasets. These results could help decide how to power future external validation studies.

The feeding siblings questionnaire (FSQ): Development of a self-report tool for parents with children aged 2-5 years

Over the last decade, there have been repeated calls to expand the operationalisation of food parenting practices. The conceptualisation and measurement of these practices has been based primarily on research with parent-child dyads. One unexplored dimension of food parenting pertains to the evaluation of practices specific to feeding siblings. This study describes the development and validation of the Feeding Siblings Questionnaire (FSQ) - a tool designed to measure practices in which siblings are positioned as mediators in parents' attempts to prompt or persuade a child to eat. Item development was guided by a conceptual model derived from mixed-methods research and refined through expert reviews and cognitive interviews. These interviews were conducted in two phases, where parents responded to the questionnaire primarily to test i) the readability and relevance of each item, and ii) its overall feasibility. The instrument was completed by 330 parents (96.1% mothers) in Australia with two children aged 2-5 years, and repeated by 133 parents (40.3%) two weeks later. Exploratory factor analysis was performed on baseline data. Internal consistency and test re-test reliability of the subsequent subscales were examined. Construct validity was assessed through comparisons with existing measures of food parenting practices and child eating behaviours. The final FSQ scale included 22 items, reflecting five food parenting practices: sibling competitiveness, active sibling influence, threatening unequal division of food, sibling role modelling, and vicarious operant conditioning. Internal consistency and test re-test reliability estimates were high, and there was some evidence of convergent construct validity. While its factor structure should be confirmed in a different sample, the FSQ offers a novel tool for assessing, monitoring, and evaluating feeding interactions beyond those confined to the parent-child dyad.

Early childhood executive control modulates negative affectivity's role in increasing adolescent body mass index trajectories

BACKGROUND

Executive control and temperament have been associated with pediatric obesity. However, interactions between these constructs in relation to future weight outcomes have not been investigated.

OBJECTIVE

This longitudinal study examined early childhood executive control, early temperament (negative affectivity and surgency), and their interactions as predictors of adolescent BMI trajectories.

METHODS

At age 5.25, children (N = 229) completed executive control tasks, and parents completed the Child Behavior Questionnaire to assess temperament. BMI was calculated annually between ages 14-17.

RESULTS

Greater early negative affectivity predicted more positive BMI growth. Although early childhood executive control was not associated with BMI growth, greater negative affectivity predicted greater BMI escalation at average and below average executive control abilities.

CONCLUSIONS

For children without robust executive control abilities early in development, negative affectivity may be a risk factor for accelerated adolescent BMI growth. Targeted assessment of early risk factors may be useful for childhood obesity prevention efforts.

The role of social norms, intergroup contact, and ingroup favoritism in weight stigma

Although average body size in the U.S. has increased in recent decades, stigma directed at individuals with higher weight has not diminished. In this study, we explored this phenomenon by investigating the relationship between people's perceived social norms regarding higher weight and their reported levels of weight bias (i.e., anti-fat attitudes). Our predictions for perceived social norms drew on the concepts of intergroup contact and ingroup favoritism, which were also probed in this study. We hypothesized that both greater descriptive norms and more favorable injunctive norms regarding higher weight would be associated with lower reported weight bias. Individuals' quantity and quality of social contact with people with higher weight were also predicted to be associated with lower weight bias. Finally, we predicted that individuals who perceived themselves as heavier would display ingroup favoritism (i.e., report less weight bias). Participants (N = 272) from the United States completed a set of online questionnaires about their perceived social norms, social contact with people with higher weight, and explicit weight bias. We found support for each of these pre-registered predictions (ps < 0.03), and post hoc analyses revealed that quality, but not quantity, of social contact with individuals with higher weight was an important predictor of lower weight bias. Together, these findings provide insight into the social psychology of weight bias and help to lay a theoretical foundation for future efforts to reduce weight stigma.

Association Between Early-Life Exposure to Antibiotics and Development of Child Obesity: Population-Based Study in Italy

BACKGROUND

Childhood obesity is a significant public health problem representing the most severe challenge in the world. Antibiotic exposure in early life has been identified as a potential factor that can disrupt the development of the gut microbiome, which may have implications for obesity.

OBJECTIVE

This study aims to evaluate the risk of developing obesity among children exposed to antibiotics early in life.

METHODS

An Italian retrospective pediatric population-based cohort study of children born between 2004 and 2018 was adopted using the Pedianet database. Children were required to be born at term, with normal weight, and without genetic diseases or congenital anomalies. We assessed the timing of the first antibiotic prescription from birth to 6, 12, and 24 months of life and the dose-response relationship via the number of antibiotic prescriptions recorded in the first year of life (none, 1, 2, and ≥3 prescriptions). Obesity was defined as a BMI z score >3 for children aged ≤5 years and >2 for children aged >5 years, using the World Health Organization growth references. The obese incidence rate (IR) × 100 person-years and the relative 95% CI were computed using infant sex, area of residence, preschool and school age, and area deprivation index, which are the covariates of interest. A mixed-effect Cox proportional hazards model was used to estimate the hazard ratio and 95% CI for the association between antibiotic exposure in early life and child obesity between 24 months and 14 years of age, considering the family pediatricians as a random factor. Several subgroup and sensitivity analyses were performed to assess the robustness of our results.

RESULTS

Among 121,540 children identified, 54,698 were prescribed at least an antibiotic within the first year of life and 26,990 were classified as obese during follow-up with an incidence rate of 4.05 cases (95% CI 4.01-4.10) × 100 person-year. The risk of obesity remained consistent across different timings of antibiotic prescriptions at 6 months, 1 year, and 2 years (fully adjusted hazard ratio [aHR] 1.07, 95% CI 1.04-1.10; aHR 1.06, 95% CI 1.03-1.09; and aHR 1.07, 95% CI 1.04-1.10, respectively). Increasing the number of antibiotic exposures increases the risk of obesity significantly (P trend<.001). The individual-specific age analysis showed that starting antibiotic therapy very early (between 0 and 5 months) had the greatest impact (aHR 1.12, 95% CI 1.08-1.17) on childhood obesity with respect to what was observed among those who were first prescribed antibiotics after the fifth month of life. These results were consistent across subgroup and sensitivity analyses.

CONCLUSIONS

The results from this large population-based study support the association between early exposure to antibiotics and an increased risk of childhood obesity. This association becomes progressively stronger with both increasing numbers of antibiotic prescriptions and younger age at the time of the first prescription.

Did child obesity decline after 2016 food regulations in Chile?

We estimated trends in the prevalence of obesity and overweight among Chilean primary and secondary students before and after Chile's 2016 regulations on the marketing and availability of foods high in energy, total sugars, sodium, or saturated fat. We used data from Chile's Survey of Nutrition, which measured the body mass index (BMI) of students in government-funded schools. Using BMI thresholds defined by the World Health Organization, we calculated the prevalence of overweight and obesity for each year from 2013 to 2019 among students attending pre-kindergarten (age 4 years), kindergarten (age 5 years), first grade (6 years), and ninth grade (14 years). In ninth grade students, overweight and obesity prevalence rose by 2 percentage points over the 3 years after introduction of the 2016 regulations. In pre-kindergarten, kindergarten, and first grade, overweight and obesity fell 1 to 3 percentage points 1 year after the regulations were introduced, but rebounded to previous levels the next year. Chile's food regulations were not followed by a sustained decline in obesity in primary- and secondary-school students. Future research should examine whether and how children in Chile and other countries maintain high levels of overweight and obesity despite food regulations designed to reduce consumption of obesogenic foods and beverages.

Identifying biologically implausible values in big longitudinal data: an example applied to child growth data from the Brazilian food and nutrition surveillance system

BACKGROUND

Several strategies for identifying biologically implausible values in longitudinal anthropometric data have recently been proposed, but the suitability of these strategies for large population datasets needs to be better understood. This study evaluated the impact of removing population outliers and the additional value of identifying and removing longitudinal outliers on the trajectories of length/height and weight and on the prevalence of child growth indicators in a large longitudinal dataset of child growth data.

METHODS

Length/height and weight measurements of children aged 0 to 59 months from the Brazilian Food and Nutrition Surveillance System were analyzed. Population outliers were identified using z-scores from the World Health Organization (WHO) growth charts. After identifying and removing population outliers, residuals from linear mixed-effects models were used to flag longitudinal outliers. The following cutoffs for residuals were tested to flag those: -3/+3, -4/+4, -5/+5, -6/+6. The selected child growth indicators included length/height-for-age z-scores and weight-for-age z-scores, classified according to the WHO charts.

RESULTS

The dataset included 50,154,738 records from 10,775,496 children. Boys and girls had 5.74% and 5.31% of length/height and 5.19% and 4.74% of weight values flagged as population outliers, respectively. After removing those, the percentage of longitudinal outliers varied from 0.02% (<-6/>+6) to 1.47% (<-3/>+3) for length/height and from 0.07 to 1.44% for weight in boys. In girls, the percentage of longitudinal outliers varied from 0.01 to 1.50% for length/height and from 0.08 to 1.45% for weight. The initial removal of population outliers played the most substantial role in the growth trajectories as it was the first step in the cleaning process, while the additional removal of longitudinal outliers had lower influence on those, regardless of the cutoff adopted. The prevalence of the selected indicators were also affected by both population and longitudinal (to a lesser extent) outliers.

CONCLUSIONS

Although both population and longitudinal outliers can detect biologically implausible values in child growth data, removing population outliers seemed more relevant in this large administrative dataset, especially in calculating summary statistics. However, both types of outliers need to be identified and removed for the proper evaluation of trajectories.

Food Parenting Practices and Child Eating Behaviors in Australian Families: A Cross-Sectional Sibling Design

BACKGROUND

Research on feeding in early childhood has focused primarily on parent-child dyadic interactions, despite parents enacting these practices within the complex dynamic of the family system.

OBJECTIVE

Using a sibling design, this study aimed to assess how parents may adapt their food parenting practices for siblings in response to differences in their eating behaviors.

DESIGN

A cross-sectional online survey was conducted between October and December 2022.

PARTICIPANTS/SETTING

Data were collected from parents (97.5% women) in Australia with 2 children aged 2 to 5 years (n = 336 parents and n = 672 children).

MAIN OUTCOME MEASURES

Survey items were completed for each sibling, and included four subscales of the Children's Eating Behaviour Questionnaire and seven subscales of the Feeding Practices and Structure Questionnaire-28.

STATISTICAL ANALYSES PERFORMED

Multiple linear regression models examined associations between within-sibling pair differences in child eating behaviors and food parenting practices, adjusting for differences in child body mass index z score, age, gender, and early feeding method.

RESULTS

Within-sibling pair differences in eating behaviors were associated with differences in some food parenting practices. For the fussier sibling, parents reported using more control-based practices, including persuasive feeding, reward for eating, and reward for behavior, and less of the structure-based practice, family meal settings (P values < 0.001). Similar directions of associations were found for persuasive feeding, reward for eating, and family meal settings with siblings who were slower eaters or more satiety responsive (P values < 0.007); however, no significant differences in reward for behavior were observed in relation to sibling differences in these eating behaviors. For the more food responsive sibling, parents reported using more control-based practices, including reward for behavior and overt restriction (P values < 0.002).

CONCLUSIONS

Within families, parents may adapt certain practices in response to differences in their children's eating behaviors. Interventions promoting responsive feeding should be designed to acknowledge the integral role of siblings in shaping parents' feeding decisions.

Body height and spinal pain in adolescence: a cohort study from the Danish National Birth Cohort

OBJECTIVES

To investigate how body height and trajectories of height from infancy through childhood and adolescence were associated with spinal pain in pre- and late adolescence.

METHODS

This prospective study included 43,765 individuals born into The Danish National Birth Cohort (DNBC) from 1996 to 2003. DNBC-data were linked with health and social data identified from Statistics Denmark registers. Spinal pain was self-reported in both the 11-year- and 18-year follow-up of DNBC and classified according to severity. Body height was measured from birth and onwards and further modelled as distinct developmental height trajectories by using latent growth curve modelling. Associations were estimated by using multinomial logistic regression models.

RESULTS

Taller body height in childhood and adolescence was associated with approximately 20% increased likelihood of spinal pain in pre- and late adolescence among girls compared to their peers in the normal height group. For boys, taller body height was associated with spinal pain by late adolescence only. Spinal pain in pre-adolescence almost doubled the likelihood of spinal pain in late adolescence regardless of body height at age 18. Height trajectories confirmed the relationship for girls with the tall individuals being most likely to have spinal pain in both pre- and late adolescence.

CONCLUSION

Tall body height during childhood and adolescence predisposes to spinal pain among girls in both pre-and late adolescence, and among boys in late adolescence. Body height is a contributing factor to the pathogenesis of spinal pain in adolescence; however, the mechanisms may be related to growth velocity, but for now uncertain.

Family- and neighborhood-level environmental associations with physical health conditions in 9- and 10-year-olds

OBJECTIVE

To determine how environmental factors are associated with physical health conditions in 9- to 10-year-old participants in the Adolescent Brain Cognitive Development (ABCD) Study, and how they are moderated by family-level socioeconomic status (SES).

METHOD

We performed cross-sectional analyses of 8,429 youth participants in the ABCD Study, in which nine physical health conditions (having underweight or overweight/obesity, not participating in sports activities, short sleep duration, high sleep disturbances, lack of vigorous and strengthening-related physical activity, miscellaneous medical problems, and traumatic brain injury) were regressed on three environmental factors [neighborhood disadvantage (area deprivation index [ADI]), risk of lead exposure, and concentrations of particulate matter 2.5 (PM2.5)] and their interaction with family-level SES (i.e., parent-reported annual household income). Environmental data were geocoded to participants' primary residential addresses at 9- to 10-year-olds.

RESULTS

Risk of lead exposure and ADI were positively associated with the odds of having overweight/obesity, not participating in sports activity, and short sleep durations. ADI was also positively associated with high sleep disturbances. PM2.5 was positively associated with the odds of having overweight/obesity and reduced vigorous physical activity. Family-level SES moderated relationships between ADI and both underweight and overweight/obesity, with high SES being associated with more pronounced changes given increased ADI.

CONCLUSIONS

Policymakers and public health officials must implement policies and remediation strategies to ensure children are free from exposure to neurotoxicant and environmental factors. Physical health conditions may be less of a product of an individual's choices and more related to environmental influences. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Derivation of paediatric blood pressure percentiles from electronic health records

BACKGROUND

Identification of abnormal blood pressure (BP) in children requires normative data. We sought to examine the feasibility of using "real-world" office BP data obtained from electronic health records (EHR) to generate age-, sex- and height-specific BP percentiles for children.

METHODS

Using data collected 01/01/2009-8/31/2021 from eight large children's healthcare organisations in PEDSnet, we applied a mixed-effects polynomial regression model with random slopes to generate Z-scores and BP percentiles and compared them with currently used normative BP distributions published in the 2017 American Academy of Paediatrics (AAP) Clinical Practise Guidelines (CPG).

FINDINGS

We identified a study sample of 292,412 children (1,085,083 BP measurements), ages 3-17 years (53% female), with no chronic medical conditions, who were not overweight/obese and who were primarily seen for general paediatric care in outpatient settings. Approximately 45,000-75,000 children contributed data to each age category. The PEDSnet systolic BP percentile values were 1-4 mmHg higher than AAP CPG BP values across age-sex-height groups, with larger differences observed in younger children. Diastolic BP values were also higher in younger children; starting with age 7 years, diastolic BP percentile values were 1-3 mmHg lower than AAP CPG values. Cohen's Kappa was 0.90 for systolic BP, 0.66 for diastolic BP, and 0.80 overall indicating excellent agreement between PEDSnet and 2017 AAP CPG data for systolic BP and substantial agreement for diastolic BP.

INTERPRETATION

Our analysis indicates that real-word EHR data can be used to generate BP percentiles consistent with current clinical practise on BP management in children.

FUNDING

Funding for this work was provided by the Preserving Kidney Function in Children with Chronic Kidney Disease (PRESERVE) study; Patient-Centred Outcomes Research Institute (PCORI) RD-2020C2020338 (Principal Investigator: Dr. Forrest; Co-Principal Investigator: Dr. Denburg).

Frequency of anthropometric implausible values estimated from different methodologies: a systematic review and meta-analysis

CONTEXT

Poor anthropometric data quality affect the prevalence of malnutrition and could harm public policy planning.

OBJECTIVE

This systematic review and meta-analysis was designed to identify different methods to evaluate and clean anthropometric data, and to calculate the frequency of implausible values for weight and height obtained from these methodologies.

DATA SOURCES

Studies about anthropometric data quality and/or anthropometric data cleaning were searched for in the MEDLINE, LILACS, SciELO, Embase, Scopus, Web of Science, and Google Scholar databases in October 2020 and updated in January 2023. In addition, references of included studies were searched for the identification of potentially eligible studies.

DATA EXTRACTION

Paired researchers selected studies, extracted data, and critically appraised the selected publications.

DATA ANALYSIS

Meta-analysis of the frequency of implausible values and 95% confidence interval (CI) was estimated. Heterogeneity (I2) and publication bias were examined by meta-regression and funnel plot, respectively.

RESULTS

In the qualitative synthesis, 123 reports from 104 studies were included, and in the quantitative synthesis, 23 studies of weight and 14 studies of height were included. The study reports were published between 1980 and 2022. The frequency of implausible values for weight was 0.55% (95%CI, 0.29-0.91) and for height was 1.20% (95%CI, 0.44-2.33). Heterogeneity was not affected by the methodological quality score of the studies and publication bias was discarded.

CONCLUSIONS

Height had twice the frequency of implausible values compared with weight. Using a set of indicators of quality to evaluate anthropometric data is better than using indicators singly.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42020208977.

Health Risk and Underweight

Anorexia nervosa is associated with a significant risk of morbidity and mortality. In clinical practice, health risk is assessed and estimated using routinely collected laboratory data. This study will develop a risk score using clinically relevant laboratory parameters. The related question is how to estimate the health risk associated with underweight using body weight, height and age.

METHODS

We used routinely collected laboratory parameters from a total of 4087 patients. The risk score was calculated on the basis of electrolytes, blood count, transaminases and LDH. The nine parameters used were summed as zlog-transformed values. Where appropriate, the scales were inverted so that high values represented higher risk. For statistical prediction of the risk score, weight/height and age reference values from the WHO, the CDC (Center of Disease Control) and representative studies of German children and adults (KIGGS and NNS) were used.

RESULTS

The score calculated from nine laboratory parameters already shows a convincing relationship with BMI. Among the weight measures used for height and age, the z-score from the CDC reference population emerged as the best estimate, explaining 34% of the variance in health risk measured by the laboratory score. The percentile rank for each age-specific median weight from the KIGGS/NNS still explained more than 31% of the variance. In contrast, percentiles explained less variance than BMI without age correction.

CONCLUSIONS

The score we used from routine laboratory parameters appears to be an appropriate measure for assessing the health risk associated with underweight, as measured by the quality of the association with BMI. For estimating health risk based on weight, height and age alone, z-scores and percentages of age-specific median weight, as opposed to percentiles, are appropriate parameters. However, the study also shows that existing age-specific BMI reference values do not represent risk optimally. Improved statistical estimation methods would be desirable.

Participation in a School-Based Wellness Initiative Associated With Improved K-12 Student Body Mass Index Trends

BACKGROUND

Associations between school participation in an academic medical center-supported school-based wellness initiative and programmatic components implemented with change in average student body mass index (BMI) over time were examined.

METHODS

This was an observational study of 103 K-12 South Carolina schools over school years 2014-2018, classified as participating (n = 87 schools, 27,855 students) or non-participating (n = 16 schools; 3608 students). Associations between students' BMI z-score (BMIz) and school participation were evaluated by linear multilevel mixed-effects modeling using data from FitnessGram and the School Wellness Checklist© (SWC), respectively.

RESULTS

One-third of the students had a BMI percentile ≥85. Average student BMIz decreased in participating schools (p = .026) and increased in non-participating schools (p = .004) over time. For schools that participated two or more years, there was an inverse relationship between SWC score and student BMIz (p = .002) that did not differ by school type, rural/urban location, Title 1 status, or student sex. Physical activity and stress management interventions for students, as well as employee wellness and establishing a wellness committee at the school level were significantly associated with decreased average student BMIz (all p < .05).

CONCLUSION

Implementation of similar comprehensive school-based wellness programs focused on improving physical activity, stress management, and employee engagement may help prevent and reduce pediatric obesity in diverse communities.

Recall of food marketing on videogame livestreaming platforms: Associations with adolescent diet-related behaviours and health

Digital media has become an integral part of adolescents' lives. Mirroring this trend, food and non-alcoholic beverage (hereafter: food) brands increasingly promote products in digital media to maximise reach with young consumers. Videogame livestreaming platforms, where individuals can broadcast or watch streamed videogame footage, are a growing form of digital media. The top three platforms (market share by hours watched) are Twitch (72%), YouTube Gaming (13%), and Facebook Gaming Live (9%), with a combined 34.6 billion hours watched in 2021. These platforms represent a hybridisation of two popular digital trends amongst teenagers: viewing online video content and playing videogames. On these platforms, gaming influencers promote food brands and products, with energy drinks and fast-food restaurants representing the most frequently promoted categories. Evidence suggests that food marketing via Twitch is associated with food craving, purchasing and consumption in adults. Yet, despite the evident teenage appeal and prevalence of food marketing on these platforms, research is yet to explore its associations with adolescent eating behaviour. Adolescents (n = 490, M_age = 16.81, 30.2% female) completed an online cross-sectional questionnaire exploring their recall of food marketing on the top three videogame livestreaming platforms, and relevant behavioural (purchase, consumption) and health (Body Mass Index) outcomes. Structural equation modelling was used to explore hierarchical relationships between the key variables. Results showed that recall of unhealthy food marketing on these platforms was significantly associated with purchase and consumption of marketed food categories. Attitudes towards unhealthy foods mediated this relationship. Findings are the first to demonstrate the relationships between unhealthy food marketing via videogame livestreaming platforms and adolescent eating behaviours, which has implications for the design of policies to restrict digital food marketing to young people.

Association of decreases in PM2.5 levels due to the implementation of environmental protection policies with the incidence of obesity in adolescents: A prospective cohort study

AIMS

To explore the association between decreased levels of particulate matter (≤2.5 µm; PM_2.5) due to the implementation of environmental protection policies and the incidence of obesity in adolescents in Chongqing, China through a prospective cohort study.

METHODS

A total of 2105 children (52.02% male; aged 7.33 ± 0.60 years at baseline) were enrolled from the Chongqing Children's Health Cohort. A mixed linear regression model was used to analyse the relationships of PM_2.5 levels with obesity indicators after adjusting for covariates. Additionally, a Poisson regression model was used to determine the relationship between PM_2.5 exposure and the incidence of overweight/obesity.

RESULTS

The average PM_2.5 exposure levels from participant conception to 2014, from 2015 to 2017, and from 2018 to 2019 were 66.64 ± 5.33 μg/m³, 55.49 ± 3.78 μg/m³, and 42.50 ± 1.87 μg/m³, respectively; these levels significantly decreased over time (P < 0.001). Throughout the entire follow-up period, the incidence of overweight/obesity after a ≥ 25 μg/m³ decrease in the PM_2.5 level was 4.57% among females; this incidence was the lowest among females who experienced remarkable decreases in PM_2.5 exposure. A 1-µg/m³ decrease in the PM_2.5 level significantly decreased the body mass index (BMI), BMI z score (BMI_z), and weight of adolescents (all P < 0.001). Compared with a < 20-μg/m³ decrease in the PM_2.5 level, a ≥ 25-μg/m³ decrease protected against increased BMI (net difference= -0.93; 95% confidence interval [CI]: (-1.23,-0.63) kg/m²), BMI_z (-0.28 (-0.39, -0.17)), weight (-1.59 (-2.44, -0.74) kg), and incidence of overweight/obesity (0.48 (0.37, 0.62), P < 0.001). Moreover, compared with a < 20-μg/m³ decrease in the PM_2.5 level, a ≥ 25-μg/m³ decrease resulted in significant absolute differences in BMI (-1.26 (-1.56, -0.96) kg/m²), BMI_z (-0.53 (-0.65, -0.40)) and weight (-3.01 (-3.8, -2.19) kg) (all P < 0.001).

CONCLUSIONS

This study showed the etiological relevance of declining PM_2.5 concentrations for the incidence of obesity in children and adolescents, suggesting that controlling ambient air pollutants may prevent the development of obesity in this age group. Continuous implementation of environmental protection policies in China has led to substantial health benefits.

Association between recreational screen time and excess weight and obesity assessed with three sets of criteria in Spanish residents aged 2-14 years

INTRODUCTION AND OBJECTIVE

Studies that assess the association between excess weight and screen time in childhood and adolescence are methodologically heterogeneous, and few studies have analysed the exposure to smartphones and tablets. Our study aimed to assess the association between daily recreational screen time and excess weight (overweight+obesity) and obesity in children aged 2-14 years residing in Spain using different sets of standards.

METHODS

We conducted a cross-sectional study using data from the 2017 Spanish National Health Survey (N=4528). We assessed the prevalence of overweight and obesity applying the criteria of the World Health Organization (WHO), International Obesity Task Force (IOTF), and Orbegozo 2011 study. We categorised daily recreational screen time in minutes as 0-59, 60-119, 120-179, and ≥180. We calculated crude and adjusted prevalence ratios (aPR) of excess weight and obesity based on the daily minutes of recreational screen time with the corresponding 95% confidence intervals (95%CI). Moreover, we calculated crude and adjusted change (aΔ) in the expected number of fulfilled excess weight/obesity criteria based on the minutes of daily recreational screen time with the corresponding 95% CI. We adjusted the association analyses for potential confounders.

RESULTS

We found that spending 180min or more a day of recreational screen time was associated with an increase in the adjusted prevalence of excess weight (e.g. Orbegozo 2011 aPR_≥180, 1.20; 95% CI, 1.02-1.42) and of obesity (e.g. IOTF aPR_≥180, 1.41; 95% CI, 1.06-1.86) as well as an increase in the adjusted number of fulfilled criteria for excess weight (aΔ_≥180, 1.18; 95% CI, 1.06-1.31).

CONCLUSIONS

Longer periods of recreational screen time were associated with excess weight and obesity in children aged 2-14 years. Cohort studies are required to confirm these findings, as this may be a determinant of health in children.

A Critical Analysis of Representations of Inequalities in Childhood Obesity in Australian Health Policy Documents

BACKGROUND

In Australia, childhood obesity follows a socioeconomic gradient whereby children with lower socioeconomic position are disproportionately burdened. To reduce these inequalities in childhood obesity requires a multi-component policy-driven response. Action to address health issues is underpinned by the ways in which they are represented as 'problems' in public policy. This study critically examines representations of inequalities in childhood obesity within Australian health policy documents published between 2000-2019.

METHODS

Australia's federal, state and territory government health department websites were searched for health policy documents including healthy weight, obesity, healthy eating, food and nutrition strategies; child and youth health strategies; and broader health and wellbeing, prevention and health promotion policies that proposed objectives or strategies for childhood obesity prevention. Thematic analysis of eligible documents was guided by a theoretical framework informed by problematization theory, ecological systems theory, and theoretical principles for equity in health policy.

RESULTS

Eighteen policy documents were eligible for inclusion. The dominant representation of inequalities in childhood obesity was one of individual responsibility. The social determinants of inequalities in childhood obesity were acknowledged, yet policy actions predominantly focused on individual determinants. Equity was positioned as a principle of policy documents but was seldom mentioned in policy actions.

CONCLUSION

Current representations of inequalities in childhood obesity in Australian health policy documents do not adequately address the underlying causes of health inequities. In order to reduce inequalities in childhood obesity future policies will need greater focus on health equity and the social determinants of health (SDoH).

The Impact of PM2.5 on the Growth Curves of Children's Obesity Indexes: A Prospective Cohort Study

Aims

To explore the effect of long-term exposure to particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) on childhood obesity based on a cohort study in Chongqing.

Methods

A total of 4,284 children aged 6-8 years at baseline were enrolled from the Chongqing Children Health Cohort in 2014-2015 and were followed up in 2019. A stratified cluster sampling was applied to select the participants. A Mixed-effects linear regression model was used to examine the effect of long-term exposure to PM2.5 on the growth curve of obesity indicators [including body mass index (BMI), BMI Z-score (BMIz), and waist-to-height ratio (WHtR)]. A mixed-effects logistic regression model was used to study the dose relationship between PM2.5 exposure and the risk of obesity indicators.

Results

A higher level of accumulating exposure to PM2.5 was associated with an increased childhood obesity index, and the effect was the most significant for WHtR than BMI and BMIz. This effect was more pronounced in boys than in girls except for WHtR, and it was the most significant under the PM2.5 exposure period from pregnancy to 6 years old. Compared the annual average PM2.5 exposure level of <60 μg/m³, the WHtR and BMI were increased by 0.019 [(95% CIs): 0.014, 0.024] and 0.326 [(95% CIs): 0.037, 0.616] Kg/m² for participants living with the PM2.5 exposure level of 70-75 μg/m³, respectively. For every 5 μg/m³ increase in PM2.5 levels (from pregnancy to 6 years old), the risk of central obesity was increased by 1.26 {odds ratio [OR] (95% CIs): 1.26 (1.16, 1.37), p < 0.001} times.

Conclusions

This study confirmed a dose-response relationship between PM2.5 exposure and childhood obesity, especially central obesity, suggesting that controlling ambient air pollution can prevent the occurrence of obesity in children and adolescents.

Thromboembolic Outcomes in Tetrahydrocannabinol-Positive Trauma Patients With Traumatic Brain Injury

INTRODUCTION

Traumatic brain injury (TBI) is a significant source of morbidity and mortality in the United States. Recent shifts in state legislation have increased the use of recreational and medical marijuana. While cannabinoids and tetrahydrocannabinol (THC) have known anti-inflammatory effects, the impact of preinjury THC use on clinical outcomes in the setting of severe TBI is unknown. We hypothesized that preinjury THC use in trauma patients suffering TBI would be associated with decreased thromboembolic events and adverse outcomes.

METHODS

The American College of Surgeons Trauma Quality Improvement Program was used to identify patients aged ≥18 y with TBI and severe injury (Injury Severity Score ≥ 16) in admit year 2017. Patients with smoking or tobacco history or missing or positive toxicology tests for drug and/or alcohol use other than THC were excluded. Propensity score matching was used to compare THC+ patients to similar THC- patients.

RESULTS

A total of 13,266 patients met inclusion criteria, of which 1669 were THC+. A total of 1377 THC+ patients were matched to 1377 THC- patients. No significant differences were found in in-hospital outcomes, including mortality, length of stay, cardiac arrest, pulmonary embolism, deep vein thrombosis, or acute respiratory distress syndrome. No patients had ischemic stroke, and THC+ patients had significantly decreased rates of hemorrhagic stroke (0.5% versus 1.5%, P = 0.02, odds ratio 0.41 [95% confidence interval 0.18-0.86]).

CONCLUSIONS

Preinjury THC use may be associated with decreased hemorrhagic stroke in severely injured patients with TBI, but there was no difference in thromboembolic outcomes. Further research into pathophysiological mechanisms related to THC are needed.

Association between Leisure Screen Time and Emotional and Behavioral Problems in Spanish Children

OBJECTIVE

To assess the relation between leisure screen time and emotional and behavioral problems in Spanish children aged 4-14 years.

STUDY DESIGN

This cross-sectional study used a representative sample of children aged 4-14 years included in the 2017 Spanish National Health Survey (n = 4073). Emotional and behavioral problems of children were assessed through the parent-report Strengths and Difficulties Questionnaire. Daily leisure screen time in minutes was categorized as 0-59, 60-119, 120-179, and ≥180. We calculated adjusted prevalence ratios (aPR) and their 95% CIs of being at risk of developing emotional and behavioral problems. Associations were adjusted for potential confounding variables.

RESULTS

Children spending 180 minutes or more of daily leisure screen time compared with children spending less than 1 hour were more likely to be at risk of developing emotional and behavioral problems: aPR_≥180: 2.19 (95% CI 1.53-3.14), emotional symptomology: aPR_≥180: 2.09 (95% CI 1.37-3.18), conduct problems aPR_≥180: 1.85 (95% CI 1.34-2.54), peer problems aPR_≥180: 1.78 (95% CI 1.15-2.75), and to behave less prosocially: aPR_≥180: 2.20 (95% CI 1.43-3.37).

CONCLUSIONS

We have found significant associations between daily leisure screen time and emotional and behavioral problems in Spanish children between 6 and 14 years of age. However, these findings should be confirmed in cohort studies, so institutions might consider including screen time as a new risk factor for children.

Context, importance, and process for creating a body mass index surveillance system to monitor childhood obesity within the New York City public school setting

The Office of School Health, a joint program of the Departments of Health and Education, administers New York City’s (NYC) body mass index (BMI) surveillance system to monitor childhood obesity. We describe the context, importance, and process for creating a multi-agency, school-based BMI surveillance system using BMI collected from annual FITNESSGRAM® physical fitness assessments conducted as part of a larger physical activity and wellness curriculum in NYC public schools. We also summarize our current system and methodology, highlighting the types of data and data sources that comprise the system and partnership between the Departments of Health and Education that enable data sharing. Strategies for addressing threats to data quality, including missing data, biologically implausible values, and imprecise/subjective weight or height equipment are discussed. We also review current and future surveillance data products, and provide recommendations for collecting, analyzing, interpreting, and reporting BMI data for childhood obesity surveillance. Collaboration between Departments of Health and Education as well as attention to safeguards of BMI reporting and data quality threats have enabled NYC to collect high quality BMI data to accurately monitor childhood obesity trends. These findings have implications for youth BMI surveillance systems in the United States and globally.

A Comprehensive Overview of the Physical Health of the Adolescent Brain Cognitive Development Study Cohort at Baseline

Physical health in childhood is crucial for neurobiological as well as overall development, and can shape long-term outcomes into adulthood. The landmark, longitudinal Adolescent Brain Cognitive Development StudySM (ABCD study®), was designed to investigate brain development and health in almost 12,000 youth who were recruited when they were 9-10 years old and will be followed through adolescence and early adulthood. The overall goal of this paper is to provide descriptive analyses of physical health measures in the ABCD study at baseline, including but not limited to sleep, physical activity and sports involvement, and body mass index. Further this summary will describe how physical health measures collected from the ABCD cohort compare with current normative data and clinical guidelines. We propose this data set has the potential to facilitate clinical recommendations and inform national standards of physical health in this age group. This manuscript will also provide important information for ABCD users and help guide analyses investigating physical health including new avenues for health disparity research as it pertains to adolescent and young adult development.

Prediction of early childhood obesity with machine learning and electronic health record data

OBJECTIVE

This study compares seven machine learning models developed to predict childhood obesity from age > 2 to ≤ 7 years using Electronic Healthcare Record (EHR) data up to age 2 years.

MATERIALS AND METHODS

EHR data from of 860,510 patients with 11,194,579 healthcare encounters were obtained from the Children's Hospital of Philadelphia. After applying stringent quality control to remove implausible growth values and including only individuals with all recommended wellness visits by age 7 years, 27,203 (50.78 % male) patients remained for model development. Seven machine learning models were developed to predict obesity incidence as defined by the Centers for Disease Control and Prevention (age/sex adjusted BMI>95th percentile). Model performance was evaluated by multiple standard classifier metrics and the differences among seven models were compared using the Cochran's Q test and post-hoc pairwise testing.

RESULTS

XGBoost yielded 0.81 (0.001) AUC, which outperformed all other models. It also achieved statistically significant better performance than all other models on standard classifier metrics (sensitivity fixed at 80 %): precision 30.90 % (0.22 %), F1-socre 44.60 % (0.26 %), accuracy 66.14 % (0.41 %), and specificity 63.27 % (0.41 %).

DISCUSSION AND CONCLUSION

Early childhood obesity prediction models were developed from the largest cohort reported to date. Relative to prior research, our models generalize to include males and females in a single model and extend the time frame for obesity incidence prediction to 7 years of age. The presented machine learning model development workflow can be adapted to various EHR-based studies and may be valuable for developing other clinical prediction models.

Association between Leisure Screen Time and Junk Food Intake in a Nationwide Representative Sample of Spanish Children (1-14 Years): A Cross-Sectional Study

Evidence on the association between new patterns of leisure screen time and junk food consumption in Spanish children at the national level is scarce. The aim of this study is to assess the relation between daily leisure screen time and the frequency of sweet, soft drink, fast food, and snack intake in a representative sample of Spanish children and adolescents aged from 1 to 14 years. We conducted a cross-sectional study using a representative sample of the Spanish population under 15 years recruited for the 2017 Spanish National Health Survey (n = 5480). We dichotomized sweet, soft drink, fast food, and snack intake (high/low) and categorized daily leisure screen time (0–59, 60–119, 120–179, and ≥180 min). We calculated crude prevalence ratios and adjusted prevalence ratios, and their 95% confidence intervals (95% CI), of high frequency of sweet, soft drink, fast food, and snack intake. Children spending at least one hour of daily leisure screen time had higher prevalence of high frequency of sweet and snack intake than children being exposed less than one hour. For soft drinks and fast food, prevalence of high frequency intake was significantly higher from two and three hours of exposure, respectively. Longer periods of screen exposure in Spanish children during their leisure time may be associated with poorer dietary behaviors. The negative effects of excessive screen time in pediatrics population should be further studied.

Indirect Associations Between Commercial Television Exposure and Child Body Mass Index

OBJECTIVE

To formally test a hierarchy of effects model linking exposure to television (TV) advertising for unhealthy foods with child body weight through purchase requests, purchases, and consumption.

DESIGN

A nationally representative cross-sectional online study in the United Kingdom.

PARTICIPANTS

A total of 2,260 parent-child dyads (children aged 7-11 years) recruited via online research panel; 55.7% boys, mean age 8.9 ± 1.4 years, mean body mass index z-score 1.25 ± 2.1.

MAIN OUTCOME MEASURES

Parents reported on child TV exposure and child height and weight. Children self-reported their frequency of (1) pestering for advertised foods, (2) purchase of unhealthy foods, and (3) consumption of unhealthy foods.

ANALYSIS

A structural equation model was applied to data.

RESULTS

As predicted, commercial TV exposure was indirectly associated with children's body mass index through purchasing and consumption through purchase requests. It was also directly associated with children's purchase requests, purchasing, and consumption of unhealthy foods. Associations between noncommercial TV and behavior or body weight outcomes, when found, were significantly weaker than for commercial exposure.

CONCLUSIONS AND IMPLICATIONS

This study provides insight into the likely behavioral pathways underpinning the effects of food marketing on diet and potentially body weight in children. Future longitudinal analyses would provide insight into causal inferences.

Association of screen time and sleep duration among Spanish 1-14 years old children

BACKGROUND

Due to the change in screen time usage in the last decade, there is needed to add more evidence about the relationship of screen time and sleep duration.

OBJECTIVE

To assess the association between screen time and sleep duration among Spanish children between 1 and 14 years old.

METHODS

We used data from the 2017 Spanish National Health survey, conducted on a representative sample of the Spanish population. We categorised daily leisure screen time as 0-59, 60-119, 120-179, and ≥180 minutes. We classified sleep duration, depending on the age, as proper sleep duration and short sleep duration. We calculated unadjusted, and adjusted prevalence ratio (PR) and 95% confidence interval (CI) of short sleep duration according to daily leisure screen time after adjusting for potential confounders. PR's were derived from fitting generalised linear models with Poisson distribution and robust variance.

RESULTS

Of the 5517 Spanish children aged 1-14 years, 44.3% spent 120 minutes or more of daily leisure screen time and 23.6% had short sleep duration. 24.5% and 28.2% of children spending between 120 and 179 minutes and exceeding 180 minutes of daily leisure screen time suffered short sleep duration, respectively. In the adjusted model, higher patterns of daily leisure screen time were associated with short sleep duration: adjusted PR_120-179  = 1.34 (95% CI 1.18, 1.54) and adjusted PR_≥180  = 1.48 (95% CI 1.27, 1.73).

CONCLUSIONS

Around one out of four Spanish children between 1 and 14 years old, exceeding 120 minutes of daily leisure screen time, had short sleep duration. More scientific research is needed for institutions to work on providing novel healthcare programmes that consider these new determinants of child health.

Symptoms of disordered eating and participation in individual- and team sports: A population-based study of adolescents

AIM

This study aimed to investigate individual and team sports participation across sex, age, and levels of body mass index (BMI). We also wanted to explore how symptoms of disordered eating (DE) were associated with participation in individual and team sports, and to what extent BMI moderated this association.

METHODS

Data stemmed from a large population-based survey of 10,172 Norwegian adolescents aged 16 to 19 years. Self-reported participation in organized team- and individual sports were the dependent variables. Self-reported symptoms of DE using the five-item Eating Disturbance Screening (EDS-5) questionnaire comprised the independent variable. Covariates included sex, age, socioeconomic status, and BMI. We used regression analyses for associations between DE symptoms and sports participation, including the interaction between DE and BMI.

RESULTS

Boys had higher team sports participation compared with girls. Individual and team sports participation varied significantly across BMI levels for each sex. Symptoms of DE were negatively associated with team sports participation (odds ratio [OR] = 0.90, p < 0.001), and were not significantly associated with individual sports participation. BMI scores moderated the association between DE symptoms and individual sports participation (p < 0.005). DE symptoms were associated with higher individual sports participation among individuals with low BMI, and with lower participation among those with high BMI.

CONCLUSIONS

DE symptoms are important correlates of sports participation among adolescents, but the direction of these associations partly differs across the weight spectrum. Promotion of factors that counteract DE is needed alongside efforts to increase physical activity and sports participation in the general adolescent population.

Longitudinal association of a body mass index (BMI) genetic risk score with growth and BMI changes across the life course: The Cardiovascular Risk in Young Finns Study

BACKGROUND

The role of genetic risk scores associated with adult body mass index (BMI) on BMI levels across the life course is unclear. We examined if a 97 single nucleotide polymorphism weighted genetic risk score (wGRS97) associated with age-related progression in BMI at different life stages and distinct developmental trajectories of BMI across the early life course.

METHODS

2188 Cardiovascular Risk in Young Finns Study participants born pre-1980 who had genotype data and objective measurements of height and weight collected up to 8 times from age 6 to 49 years. Associations were examined using Individual Growth Curve analysis, Latent Class Growth Mixture Modelling, and Poisson modified regression.

RESULTS

The wGRS97 associated with BMI from age 6 years with peak effect sizes observed at age 30 years (females: 1.14 kg/m²; males: 1.09 kg/m² higher BMI per standard deviation increase in wGRS97). The association between wGRS97 and BMI became stronger with age in childhood but slowed in adolescence, especially in females, and weakened at age 35-40 years. A higher wGRS97 associated with an increased BMI velocity in childhood and adulthood, but not with BMI change in adulthood. Compared with belonging to a 'normal stable' life-course trajectory group (normal BMI from childhood to adulthood), a one standard deviation higher wGRS97 associated with a 13-127% increased risk of belonging to a less favourable life-course BMI trajectory group.

CONCLUSIONS

Individuals with genetic susceptibility to higher adult BMI have higher levels and accelerated rates of increase in BMI in childhood/adolescence, and are at increased risk of having a less favourable life-course BMI trajectory.

Rising prevalence of BMI ≥40 kg/m2 : A high-demand epidemic needing better documentation

Whilst previously rare, some surveys indicate substantial increases in the population with body mass index (BMI) ≥40 kg/m2 since the 1980s. Clinicians report emerging care challenges for this population, often with high resource demands. Accurate prevalence data, gathered using reliable methods, are needed to inform health care practice, planning, and research. We searched digitally for English language sources with measured prevalence data on adult BMI ≥40 collected since 2010. The search strategy included sources identified from recent work by NCD-RisC (2017), grey sources, a literature search to find current sources, and digital snowball searching. Eighteen countries, across five continents, reported BMI ≥40 prevalence data in surveys since 2010: 12% of eligible national surveys examined. Prevalence of BMI ≥40 ranged from 1.3% (Spain) to 7.7% (USA) for all adults, 0.7% (Serbia) to 5.6% (USA) for men, and 1.8% (Poland) to 9.7% (USA) for women. Limited trend data covering recent decades support significant growth of BMI ≥40 population. Methodological limitations include small samples and data collection methods likely to exclude people with very high BMIs. BMI ≥40 data are not routinely reported in international surveys. Lack of data impairs surveillance of population trends, understanding of causation, and societal provision for individuals living with higher weights.

Is it time to stop sweeping data cleaning under the carpet? A novel algorithm for outlier management in growth data

All data are prone to error and require data cleaning prior to analysis. An important example is longitudinal growth data, for which there are no universally agreed standard methods for identifying and removing implausible values and many existing methods have limitations that restrict their usage across different domains. A decision-making algorithm that modified or deleted growth measurements based on a combination of pre-defined cut-offs and logic rules was designed. Five data cleaning methods for growth were tested with and without the addition of the algorithm and applied to five different longitudinal growth datasets: four uncleaned canine weight or height datasets and one pre-cleaned human weight dataset with randomly simulated errors. Prior to the addition of the algorithm, data cleaning based on non-linear mixed effects models was the most effective in all datasets and had on average a minimum of 26.00% higher sensitivity and 0.12% higher specificity than other methods. Data cleaning methods using the algorithm had improved data preservation and were capable of correcting simulated errors according to the gold standard; returning a value to its original state prior to error simulation. The algorithm improved the performance of all data cleaning methods and increased the average sensitivity and specificity of the non-linear mixed effects model method by 7.68% and 0.42% respectively. Using non-linear mixed effects models combined with the algorithm to clean data allows individual growth trajectories to vary from the population by using repeated longitudinal measurements, identifies consecutive errors or those within the first data entry, avoids the requirement for a minimum number of data entries, preserves data where possible by correcting errors rather than deleting them and removes duplications intelligently. This algorithm is broadly applicable to data cleaning anthropometric data in different mammalian species and could be adapted for use in a range of other domains.

Physical fitness and nutritional status in female adolescents with anorexia nervosa

ABSTRACT Objective This study aimed to determine whether physical fitness is related to nutritional status in a sample of female adolescents with anorexia nervosa, to contrast the nourished and undernourished patients, and to compare the physical fitness in these patients with normative data of healthy subjects stratified by age and gender. Methods Nutritional status was determined using the body mass index Z-score, fat mass, fat-free mass (bioelectrical impedance analysis), and the Controlling Nutritional Status score in 15 anorexic adolescents with 14.3±1.6 years. Physical fitness was assessed using the ALPHA-Fitness Battery (handgrip strength, standing broad jump, 4x10m shuttle run, and 20m shuttle run tests). Results Handgrip strength was significantly associated with all variables of nutritional status, except with the three blood components of the Controlling Nutritional Status score. The undernourished anorexic patients showed significantly worse physical fitness than the nourished anorexic patients in all tests, except in the standing broad jump and the 4x10m shuttle run tests. The physical fitness tests of the female anorexic adolescents showed scores significantly worse than those of the normative European female adolescent population. Conclusion The observation of female adolescents with anorexia nervosa showed associations between higher physical fitness levels and better nutritional statuses. Handgrip strength and 20m shuttle run tests may be options of additional indicators of undernutrition in anorexic female adolescents. The undernourished anorexic patients showed worse physical fitness than the nourished ones. According to normative data for healthy sex- and agematched adolescents, physical fitness is severely impaired in anorexic female adolescents.

Does exclusion of extreme reporters of energy intake (the "Goldberg cutoffs") reliably reduce or eliminate bias in nutrition studies? Analysis with illustrative associations of energy intake with health outcomes

BACKGROUND

The Goldberg cutoffs are used to decrease bias in self-reported estimates of energy intake (EISR). Whether the cutoffs reduce and eliminate bias when used in regressions of health outcomes has not been assessed.

OBJECTIVE

We examined whether applying the Goldberg cutoffs to data used in nutrition studies could reliably reduce or eliminate bias.

METHODS

We used data from the Comprehensive Assessment of Long-Term Effects of Reducing Intake of Energy (CALERIE), the Interactive Diet and Activity Tracking in American Association of Retired Persons (IDATA) study, and the National Diet and Nutrition Survey (NDNS). Each data set included EISR, energy intake estimated from doubly labeled water (EIDLW) as a reference method, and health outcomes including baseline anthropometric, biomarker, and behavioral measures and fitness test results. We conducted 3 linear regression analyses using EISR, a plausible EISR based on the Goldberg cutoffs (EIG), and EIDLW as an explanatory variable for each analysis. Regression coefficients were denoted ${\hat{\beta }_{\rm SR}}$, ${\hat{\beta }_{\rm G}}$, and ${\hat{\beta }_{\rm DLW}}$, respectively. Using the jackknife method, bias from ${\hat{\beta }_{\rm SR}}$ compared with ${\hat{\beta }_{\rm DLW}}$ and remaining bias from ${\hat{\beta }_{\rm G}}$ compared with ${\hat{\beta }_{\rm DLW}}$ were estimated. Analyses were repeated using Pearson correlation coefficients.

RESULTS

The analyses from CALERIE, IDATA, and NDNS included 218, 349, and 317 individuals, respectively. Using EIG significantly decreased the bias only for a subset of those variables with significant bias: weight (56.1%; 95% CI: 28.5%, 83.7%) and waist circumference (WC) (59.8%; 95% CI: 33.2%, 86.5%) with CALERIE, weight (20.8%; 95% CI: -6.4%, 48.1%) and WC (17.3%; 95% CI: -20.8%, 55.4%) with IDATA, and WC (-9.5%; 95% CI: -72.2%, 53.1%) with NDNS. Furthermore, bias significantly remained even after excluding implausible data for various outcomes. Results obtained with Pearson correlation coefficient analyses were qualitatively consistent.

CONCLUSIONS

Some associations between EIG and outcomes remained biased compared with associations between EIDLW and outcomes. Use of the Goldberg cutoffs was not a reliable method for eliminating bias.

Association of Clinician Behaviors and Weight Change in School-Aged Children

INTRODUCTION

This study uses clinical practice data to determine whether recommended weight management clinician behaviors are associated with weight status improvement in children aged 6-12 years who are overweight or obese.

METHODS

Electronic health record data (2009-2014) from 52 clinics were used. Weight status was examined from 1 visit to the next as dichotomous improvement (versus worsening or no change) and change in percentage overweight (over sex/age-specific BMI95). The primary predictor was a clinician behavior variable denoting attention to high BMI alone or with assessment of medical risk/comorbidities and was defined using combinations of diagnostic codes and electronic health record orders. Covariates included time between visits and medications associated with weight gain or loss. Adjusted multilevel regression models examined the association of the clinician behavior variable with weight status improvement. Analyses were conducted from 2015 to 2018.

RESULTS

Children (n=7,205) had a mean age of 8.9 years; 45.5% were overweight, 54.5% obese, and 81.1% publicly insured. For 62% of overweight children, and 38%, 21%, and 11% of those in obesity classes 1-3, respectively, no attention to high BMI/medical risk assessment at any visit was identified. Children with evidence of clinician attention to high BMI alone and who underwent a medical risk assessment had significantly greater AOR of improvement in percentage of BMI95 and percentage of BMI95 change: BMI alone, AOR=1.2 (p<0.001) and β= -0.3 (p>0.05); BMI/medical risk, AOR=1.2 and β= -0.5 (both p<0.001). Other factors associated with weight status improvement included prescription medications (1 or more prescriptions associated with either weight loss or none associated with weight gain) and fewer months between visits.

CONCLUSIONS

This is the first study to use electronic health record data to demonstrate that widely recommended clinician behaviors are associated with weight status improvement in children aged 6-12 years who are overweight or obese.

New-onset diabetes after pediatric heart transplantation: A review of the Pediatric Heart Transplant Study

NDT is a well-defined complication after solid organ transplantation. Little has been published describing the incidence, risk factors, and effect on outcome after pediatric heart transplantation. We performed a retrospective evaluation of pediatric patients from the PHTS registry from 2004 to 2014. Group comparison, associated factors, incidence using Kaplan-Meier method, and risk factor and outcome analysis for NDT at 1 year post-transplant. Of the 2185 recipients, 1756 were alive and followed at 1 year. Overall freedom from NDT was 98.9%, 94.7%, and 92.6% at 1, 5, and 10 years, respectively. Patients with NDT were more likely to be black (non-Hispanic; P = 0.002), older at time of transplant (P < 0.0001), and have a higher BMI percentile at time of transplant (P < 0.0001). Adjusted risk factors for NDT at 1 year were older age at transplant (years; >12 years, OR: 8.8 and 5-12 years, HR: 8.0), obese BMI percentile at time of transplant (OR: 3.8), and steroid use at 30 days after transplant (OR: 4.7). Though uncommon, NDT occurs with a constant hazard after pediatric heart transplant; it occurs more often in older patients at transplant, those who are of black race, those who are obese, and those who use steroids. Therefore, targeted weight reduction and selective steroid use in at-risk populations could reduce the incidence of early NDT. Further data are needed to determine the risk imparted by transplantation, factors that predict late-onset NDT, and whether NDT alters the outcome after transplant.

School Food Environment, Food Consumption, and Indicators of Adiposity Among Students 7-14 Years in Bogotá, Colombia

BACKGROUND

In Colombia, the prevalence of overweight/obesity in children has increased by 26% in the past 5 years. School food environment may be an important contributor and offers opportunities for effective intervention.

METHODS

We conducted a cross-sectional study among 7- to 14-year-old schoolchildren from 10 schools in Bogotá, Colombia. We examined the school food environment and the relationship of individual-level consumption, and physical activity with overweight/obesity, measured by body mass index and percentage body fat.

RESULTS

Schools with a restaurant/store were characterized as having excessive unhealthy foods. In the sample of 714 schoolchildren, 17.5% were overweight and 10.5% were obese. In multivariate models, boys had significantly increased odds of being overweight/obese (odds ratio [OR]: 1.53; p = .01) as compared to girls. Schoolchildren who consumed a greater number of energy drinks (OR = 1.82; p = .04), and those who spent more than 3 hours per schoolday watching TV (OR = 1.53; p < .01) had increased odds of being overweight/obese.

CONCLUSIONS

Approximately 1 in 4 schoolchildren were overweight/obese, with boys, energy drink consumers, and those with low physical activity having increased risk. School-based interventions focused on improving food options and providing health behavior education may be effective to reduce overweight among children in Bogotá and similar settings.

The trends and prevalence of obesity and morbid obesity among Australian school-aged children, 1985-2014

AIM

Children with obesity have a greater risk of adverse social and physical health outcomes. We examined temporal changes in body mass index (BMI) z-scores and the prevalence obesity and morbid obesity in children from 1985 to 2014.

METHODS

Secondary data analysis of BMI data for children aged 7-15 years from five cross-sectional Australian datasets. Changes in age- and gender-adjusted BMI (BMI z-scores) and nutritional status were categorised using the International Obesity Task Force cut-off points.

RESULTS

The percentage of children who were obese tripled between 1985 and 1995 from 1.6 to 4.7%, before plateauing between 1995 and 2014. The percentage of morbidly obese children was <1% in 1985 and 1995, increasing to 2% between 1995 and 2007, with no further increase between 2007 and 2014. The proportion of obese children classified as morbidly obese was 12% in 1985-1995, 24% in 2007-2012 and 28% in 2014. Between 1985 and 2012, the mean BMI z-score increased in children categorised as obese from 1.94 (standard deviation 0.15) to 2.03 (0.22), and then plateaued. For morbidly obese children, the mean BMI z-score was 2.4 (0.13) and remained similar over the study period.

CONCLUSIONS

Our findings suggest that the relative fatness of children with morbid obesity, as measured by BMI z-score, has remained stable. The proportion of obese and morbidly obese children has also plateaued between 2007 and 2014. However, the prevalence of obesity remains high, and more dedicated resources are required to treat children with obesity to reduce the short- and long-term health impact.

Longitudinal Associations Between Anhedonia and Body Mass Index Trajectory Groups Among Adolescents

PURPOSE

Although evidence suggests that anhedonia-a reduced ability to experience pleasure in response to rewarding stimuli-may predict weight gain during adolescence, it remains unclear whether changes in anhedonia during adolescence are associated with changes in body mass index (BMI). This study examines longitudinal associations between changes in anhedonia and developmental trajectories of BMI during adolescence.

METHODS

Self-report measures of anhedonia and BMI were collected at five semiannual assessments among students from 10 high schools in Los Angeles, CA, area (N = 3,396) followed up from the 9th grade to the 11th grade. Four BMI trajectories were identified using growth mixture modeling: (1) stable normative weight; (2) overweight to normative weight (i.e., decreasing BMI); (3) overweight to chronically obese (increasing BMI); and (4) normative weight to overweight (increasing BMI). Latent growth curve modeling estimated baseline level and changes in anhedonia. A multinomial logistic regression model tested associations of baseline level and slope of anhedonia with the four BMI trajectory groups.

RESULTS

Compared with the stable normative BMI trajectory group, each 1-unit standard deviation increase in anhedonia slope increased the odds of membership in the overweight to chronically obese group (odds ratio [OR] [95% confidence interval {CI}] = 1.29 [1.09-1.49], p < .001) and in the normative weight to overweight group (OR [95% CI] = 1.28 [1.04-1.53], p = .006), and decreased the odds of membership in the overweight to normative weight group (OR [95% CI] = .78 [.57-.95], p = .01).

CONCLUSIONS

Across a 2-year period of high school, the rate of change in anhedonia is associated with certain BMI trajectories linked with poorer metabolic health. Increasing anhedonia may be an important risk factor to consider in adolescent obesity prevention.

Identifying and categorizing spurious weight data in electronic medical records

Background

Spurious weights compromise the validity of summary measures, such as averages and trends. Even rare errors in weight records can undermine the utility of electronic medical record (EMR) data.

Objective

We sought to estimate the prevalence of spurious weight values in a large EMR, to ascertain the likely causes, and to develop and test straightforward algorithms for identifying spurious weight data.

Design

Using EMR data from 10,000 randomly selected patients aged ≥65 y in the VA system, we examined the percentage of weight change across various time intervals, from 1 to 3000 d. We examined descriptive results and developed 3 algorithms to categorize degree of weight change over time. On the basis of distributions, we identified cases that were most likely spurious. We manually reviewed these and categorized the type of error.

Results

The data followed the expected distributions. The algorithms reliably identified spurious weight. Approximately 0.8% of all weights in the record appeared to be spurious and ∼1 in 5 patient charts included ≥1 spurious weight value. The most common type of error involved the misentry of a single digit (e.g., 148 for 178).

Conclusions

Spurious weights are common in EMRs. Straightforward algorithms can identify and remove them, and thus enhance the reliability of EMR data.

Automated identification of implausible values in growth data from pediatric electronic health records

Objective

Large electronic health record (EHR) datasets are increasingly used to facilitate research on growth, but measurement and recording errors can lead to biased results. We developed and tested an automated method for identifying implausible values in pediatric EHR growth data.

Materials and Methods

Using deidentified data from 46 primary care sites, we developed an algorithm to identify weight and height values that should be excluded from analysis, including implausible values and values that were recorded repeatedly without remeasurement. The foundation of the algorithm is a comparison of each measurement, expressed as a standard deviation score, with a weighted moving average of a child's other measurements. We evaluated the performance of the algorithm by (1) comparing its results with the judgment of physician reviewers for a stratified random selection of 400 measurements and (2) evaluating its accuracy in a dataset with simulated errors.

Results

Of 2 000 595 growth measurements from 280 610 patients 1 to 21 years old, 3.8% of weight and 4.5% of height values were identified as implausible or excluded for other reasons. The proportion excluded varied widely by primary care site. The automated method had a sensitivity of 97% (95% confidence interval [CI], 94-99%) and a specificity of 90% (95% CI, 85-94%) for identifying implausible values compared to physician judgment, and identified 95% (weight) and 98% (height) of simulated errors.

Discussion and Conclusion

This automated, flexible, and validated method for preparing large datasets will facilitate the use of pediatric EHR growth datasets for research.

Effective nationwide school-based participatory extramural program on adolescent body mass index, health knowledge and behaviors

Background

Adolescent obesity is a major public health concern. Open to all high school students regardless of weight status, HealthCorps is a nationwide program offering a comprehensive high school-based participatory educational program to indirectly address obesity. We tested a hypothesis that the HealthCorps program would decrease BMI z-scores among overweight or obese students, and reduce obesity rates, and evaluated its effects on health knowledge and behaviors.

Methods

HealthCorps aimed to improve student knowledge and behaviors regarding nutrition quality, physical activity, sleep, breakfast intake, and mental resilience. Participating students received through HealthCorps coordinators weekly or bi-weekly classroom lessons either for a semester or a year in addition to various during- and after-school health-promoting activities and mentorship. Self-reported height and weight were collected along with questionnaires assessing knowledge and behaviors during 2013-2014 academic year among 14 HealthCorps-participating New York City high schools. This quasi experimental two-arm pre-post trial included 611 HealthCorps and 221 comparison arm students for the analytic sample. Sex-specific analyses stratified by weight status were adjusted for age and Hispanic ethnicity with clustering effects of schools and students taken into account.

Results

HealthCorps female overweight/obese and obese student had a significant decrease in BMI z-scores (post-pre delta BMI z-score = −0.16 (95%CI = (−0.26, −0.05), p = 0.004 for the former; and = −0.23 (−0.44, −0.03), p = 0.028, for the latter) whereas comparison female counterparts did not. The HealthCorps students, but not the comparison students, had a significant increase for all knowledge domains except for the breakfast realm, and reported a greater number of significant behavior changes including fruit and vegetable intake and physical activities.

Conclusions

The HealthCorps program was associated with reduced BMI z-score in overweight/obese and obese female adolescents, with enhanced health knowledge and behavior for both sexes. With its wide reach, this may be a promising program to help combat adolescent obesity in schools.

Trial registration

This study is registered as a clinical trial at the ClinicalTrials.gov registry with trial number NCT02277496 on September 10, 2014 (Retrospectively registered).

Electronic supplementary material

The online version of this article (10.1186/s12887-017-0975-9) contains supplementary material, which is available to authorized users.

Growth Tracking in Severely Obese or Underweight Children

OBJECTIVES

To illustrate the difficulties in optimal growth monitoring of children with severe obesity or underweight by using the Centers for Disease Control and Prevention (CDC) 2000 age- and sex-specific BMI percentile growth charts. We also aimed to examine the utility of a new modified CDC BMI z score chart to monitor growth in children with normal and extreme BMI percentiles by using real-life clinical scenarios.

METHODS

Modified BMI z score charts were created by using the 2000 CDC algorithm. Three cases of children with extreme BMI values and abnormal growth patterns were plotted by using the standard CDC 2000 clinical growth chart, the modified BMI z score chart, and the CDC BMI percentile chart, modified to include the percentage of the 95th percentile (%BMI_p95) curves.

RESULTS

Children with severe obesity could not be plotted on the standard CDC BMI percentile chart because their BMI points lay above the chart cutoff. Children with a low BMI (<3%) were also difficult to track on the standard BMI percentile chart. The addition of the %BMI_p95 scale to the standard BMI percentile chart allowed tracking of severely obese children; however, it did not address severely underweight children and required a change of units within the chart when transitioning from normal to obese BMIs. The modified BMI z score chart allowed uniform tracking.

CONCLUSIONS

The modified CDC z score chart is suitable for growth tracking of children with normal and extreme growth patterns; the measures correlate well with the %BMI_p95, and the chart can be incorporated easily into existing electronic health record systems for clinical use.

Tracking of BMI z Scores for Severe Obesity

BACKGROUND

Although the Centers for Disease Control (CDC) growth charts are widely used in studies of childhood obesity, BMI z scores are known to be inaccurate at values greater than the 97th percentile.

METHODS

We used longitudinal data from 6994 children in the Bogalusa Heart Study who were examined multiple times to compare tracking of 3 BMI metrics: BMI-for-sex/age z score (BMIz), BMI expressed as a percentage of the 95th percentile (%BMIp95), and levels of BMI z score that adjust for the compression of very high z scores (adjusted z score [BMIaz]). The later 2 metrics, unlike BMIz, do not have an upper limit. The mean interval between examinations was 2.8 years. We were particularly interested in these metrics among children with obesity or severe obesity (%BMIp95 ≥120%).

RESULTS

Although there was little difference in the tracking of the 3 metrics in the overall sample, among 247 children with severe obesity, the correlation of BMIz levels between examinations (r = 0.46) was substantially weaker than those for BMIaz and %BMIp95 (r = 0.65 and 0.61). Age-stratified analyses indicated that the weak tracking of BMIz was particularly evident before the age of 10 years (r = 0.36 vs 0.57 and 0.60). Several children with severe obesity showed BMIz decreases between examinations despite having BMI increases of over 5.

CONCLUSIONS

Among children with severe obesity, the tracking of BMIz is weak. This is because of the constraints in converting very high BMIs into z scores based on the CDC growth charts. Rather than using BMIz, it would be preferable to express very high BMIs relative to the CDC 95th percentile or to use BMIaz.

A growth reference for mid upper arm circumference for age among school age children and adolescents, and validation for mortality: growth curve construction and longitudinal cohort study

Objectives To construct growth curves for mid-upper-arm circumference (MUAC)-for-age z score for 5-19 year olds that accord with the World Health Organization growth standards, and to evaluate their discriminatory performance for subsequent mortality.Design Growth curve construction and longitudinal cohort study.Setting United States and international growth data, and cohorts in Kenya, Uganda, and Zimbabwe.Participants The Health Examination Survey (HES)/National Health and Nutrition Examination Survey (NHANES) US population datasets (age 5-25 years), which were used to construct the 2007 WHO growth reference for body mass index in this age group, were merged with an imputed dataset matching the distribution of the WHO 2006 growth standards age 2-6 years. Validation data were from 685 HIV infected children aged 5-17 years participating in the Antiretroviral Research for Watoto (ARROW) trial in Uganda and Zimbabwe; and 1741 children aged 5-13 years discharged from a rural Kenyan hospital (3.8% HIV infected). Both cohorts were followed-up for survival during one year.Main outcome measures Concordance with WHO 2006 growth standards at age 60 months and survival during one year according to MUAC-for-age and body mass index-for-age z scores.Results The new growth curves transitioned smoothly with WHO growth standards at age 5 years. MUAC-for-age z scores of -2 to -3 and less than-3, compared with -2 or more, was associated with hazard ratios for death within one year of 3.63 (95% confidence interval 0.90 to 14.7; P=0.07) and 11.1 (3.40 to 36.0; P<0.001), respectively, among ARROW trial participants; and 2.22 (1.01 to 4.9; P=0.04) and 5.15 (2.49 to 10.7; P<0.001), respectively, among Kenyan children after discharge from hospital. The AUCs for MUAC-for-age and body mass index-for-age z scores for discriminating subsequent mortality were 0.81 (95% confidence interval 0.70 to 0.92) and 0.75 (0.63 to 0.86) in the ARROW trial (absolute difference 0.06, 95% confidence interval -0.032 to 0.16; P=0.2) and 0.73 (0.65 to 0.80) and 0.58 (0.49 to 0.67), respectively, in Kenya (absolute difference in AUC 0.15, 0.07 to 0.23; P=0.0002).Conclusions The MUAC-for-age z score is at least as effective as the body mass index-for-age z score for assessing mortality risks associated with undernutrition among African school aged children and adolescents. MUAC can provide simplified screening and diagnosis within nutrition and HIV programmes, and in research.