Growth patterns from birth to overweight at age 5-6 years of children with various backgrounds in socioeconomic status and country of origin: the ABCD study

Attention-deficit/hyperactivity disorder in adolescent and adult candidates for metabolic and bariatric surgery: A systematic review and meta-analysis

AIMS

Attention-deficit with hyperactivity disorder (ADHD) is associated with obesity and impacts the outcome of metabolic and bariatric surgery (MBS). This study aimed at calculating the prevalence in candidates for MBS, which is yet unclear.

METHODS

We conducted a systematic review and meta-analysis, searching three databases from their respective inception to December 2022 for studies reporting the prevalence of ADHD in adolescents and adults assessed before undergoing MBS. The protocol was registered in PROSPERO (CRD42022384914). We adhered to Meta-analysis of Observational Studies in Epidemiology (MOOSE) and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines; the quality of studies was assessed with the JBI Critical Appraisal checklist. Random-effect meta-analyses were performed; confidence intervals were computed with a binomial exact method, and the pooled estimate was calculated after double arcsine transformation.

FINDINGS

Fourteen studies (24,455 adults) and three studies (299 adolescents) were selected. The quality of studies was moderate to poor; meta-analyses were performed on subgroups according to the case definition used. The prevalence is 8.94% and 9.90% in adults, and 28.73% in adolescents.

CONCLUSIONS

ADHD is three times more frequent in adults and six times more frequent in adolescents than in the general population. Recommendations are provided to improve the quality of future studies and obtain more reliable estimates of prevalence.

Population trajectories and age-dependent associations of obesity risk factors with body mass index from childhood to adolescence across European regions: A two-cohort study

OBJECTIVE

To investigate population trajectories of behavioural risk factors of obesity from childhood to adolescence and their associations with body mass index (BMI) in children across European regions.

METHODS

Data were harmonised between the European multi-centre IDEFICS/I.Family and the Amsterdam Born Children and their Development Cohort. Participants were aged 2.0-9.9 and 5.0-7.5 years at baseline, respectively, and were followed until age 18 years. Behavioural risk factors of interest included diet, physical activity, media use and sleep. Mixed effects models were used for statistical analyses to account for repeated measurements taken from the same child.

RESULTS

The study included a total of 14 328 individuals: 4114, 4582, 3220 and 2412 participants from Northern, Southern, Eastern Europe and Amsterdam, respectively. Risk factor means and prevalences changed with age, but the trajectories were mostly similar across regions. Almost no associations between behavioural factors and BMI were found at the age of 6 years. At 11 years, daily sugar-sweetened foods consumption, use of active transport, sports club membership and longer nocturnal sleep duration were negatively associated with BMI in most regions; positive associations were found with media use. Most associations at 11 years of age persisted to 15 years.

CONCLUSIONS

Whilst population trajectories of media use and nocturnal sleep duration are similar across European regions, those of other behavioural risk factors like active transport and daily vegetable consumption differ. Also, associations between behavioural risk factors and BMI become stronger with age and show similar patterns across regions.

Modelling individual infancy growth trajectories to predict excessive gain in BMI z-score: a comparison of growth measures in the ABCD and GECKO Drenthe cohorts

BACKGROUND

Excessive weight gain during childhood is a strong predictor for adult overweight, but it remains unknown which growth measures in infancy (0-2 years of age), besides predictors known at birth, are the strongest predictors for excessive weight gain between 2 and 5-7 years of age.

METHODS

The Amsterdam Born Children and their Development (ABCD) study formed the derivation cohort, and the Groningen Expert Center for Kids with Obesity (GECKO) Drenthe study formed the validation cohort. Change (Δ) in body mass index (BMI) z-score between 2 and 5-7 years was the outcome of interest. The growth measures considered were weight, weight-for-length (WfL), and body mass index (BMI). Formats considered for each growth measure were values at 1, 6, 12, and 24 months, at the BMI peak, the change between aforementioned ages, and prepeak velocity. 10 model structures combining different variable formats and including predictors at birth were derived for each growth measure, resulting in 30 linear regression models. A Parsimonious Model considering all growth measures and a Birth Model considering none were also derived.

RESULTS

The derivation cohort consisted of 3139 infants of which 373 (11.9%) had excessive gain in BMI z-score (> 0.67). The validation cohort contained 2201 infants of which 592 (26.9%) had excessive gain. Across the 3 growth measures, 5 model structures which included measures related to the BMI peak and prepeak velocity (derivation cohort area under the curve [AUC] range = 0.765-0.855) achieved more accurate estimates than 3 model structures which included growth measure change over time (0.706-0.795). All model structures which used BMI were superior to those using weight or WfL. The AUC across all models was on average 0.126 lower in the validation cohort. The Parsimonious Model's AUCs in the derivation and validation cohorts were 0.856 and 0.766, respectively, compared to 0.690 and 0.491, respectively, for the Birth Model. The respective false positive rates were 28.2% and 20.1% for the Parsimonious Model and 70.0% and 74.6% for the Birth Model.

CONCLUSION

Models' performances varied significantly across model structures and growth measures. Developing the optimal model requires extensive testing of the many possibilities.

Intrauterine and Extrauterine Environmental PM2.5 Exposure Is Associated with Overweight/Obesity (O/O) in Children Aged 6 to 59 Months from Lima, Peru: A Case-Control Study

There is evidence that PM2.5 could be obesogenic. Lima is one of the most polluted cities in South America, with an increasing prevalence of childhood obesity. This study aimed to determine the association between PM2.5 exposure of children aged 6 to 59 months and being overweight or obese (O/O) in a significant dataset survey. Cases were defined when weight for height Z-score (WHZ) was >2 standard deviations (SD) from the mean, for each sex. A control was defined when WHZ was between ±2 SD. We used a conditional logistic regression model to calculate the odds ratio (OR) between extrauterine and intrauterine PM2.5 exposure and O/O. Extrauterine PM2.5 exposure was evaluated as a 6-month PM2.5 mean prior to the survey. We found a significant association between O/O and extrauterine (OR: 1.57, 1.51−1.63) and intrauterine (OR: 1.99, 1.88−2.12) PM2.5 exposure for an increment of 10 μg/m3. The ORs increased as the quartile increased in both exposures. We observed a higher association in children aged 6−11 months (OR: 3.07, 2.84−3.31). In conclusion, higher levels of PM2.5 in Lima and Callao were associated with cases of O/O in children from 6 to 59 months, with the association higher for prenatal exposure.

Screen Time and Body Mass Index Among Children and Adolescents: A Systematic Review and Meta-Analysis

Background

There is no summative quantitative study that report the difference in BMI in high screen user children and adolescents or give a difference in screen time in children and adolescents with obesity vs. children and adolescents without obesity. In the current meta-analysis we systematically summarized the association between obesity and screen time and meta-analyzed the results.

Methods

A systematic search from Scopus, PubMed and Embase electronic databases. Studies that evaluated the association between screen time and obesity up to June 2021.

Results

Results revealed that those at the highest screen time category had 0.7 kg/m2 higher BMI (WMD = 0.703; CI = 0.128, 1.278; P < 0.016; I 2 = 95.8%). Moreover, children and adolescents with obesity had a mean value of 0.313 h higher screen time compared with children and adolescents without obesity (WMD: 0.313; OR = 0.219, 0.407; P < 0.001; I 2 = 96%). The results of subgrouping showed that study quality, continent and sample size could reduce the heterogeneity values. No evidence of publication bias was reported according to visual asymmetry of funnel plots and the results of Begg's and Egger's tests.

Conclusion

For the first time, the current systematic review and meta-analysis revealed a positive association between screen time and obesity among children and adolescents. Due to the cross-sectional design of the included studies, causal inference is impossible, therefore, further studies in separate analysis of both genders are suggested to better elucidate gender-specific results.

Systematic Review Registration

[www.ClinicalTrials.gov], identifier [CRD4202123 3899].

Investigating socioeconomic inequalities in BMI growth rates during childhood and adolescence

BACKGROUND

Many countries report socioeconomic inequalities in childhood obesity, but when they develop is not well-characterised. Studies rarely isolate BMI growth rates from overall BMI, perhaps overlooking an important precursor to the observed inequalities in obesity. The objective of this study was to determine the age at which inequalities in BMI growth rates develop in children and whether they are similar across the BMI spectrum.

METHODS

Using the Longitudinal Study of Australian Children (n = 9024), a cohort study, we measured socioeconomic inequalities in annual BMI growth from age 2 to 17 years by age, sex and weight status. We fit a linear model using generalised estimating equations (GEE) to estimate simultaneously the effects of age and weight status on inequalities in BMI growth rate.

RESULTS

The slope (SII) and relative (RII) indexes of inequality for annual BMI growth were greatest in middle childhood (age 4-11 years) (SII 0.25, RII 1.83 (boys) 1.78 (girls)) and were moderate during adolescence (age 10-17 years) (SII 0.11, RII 1.16 [boys] 1.15 [girls]). In early childhood, there was little evidence of inequality in annual BMI growth except in children with obesity. In middle childhood and adolescence, inequalities were greater at higher weight status. The GEE indicated that both weight status (P < 0.001) and age period (P < 0.001) affected inequalities in BMI growth rates.

CONCLUSIONS

Inequalities in annual BMI growth were strongest in middle childhood, and widest in children at the upper end of the BMI spectrum. This could signify a key age bracket to intervene clinically and at a public health level and improve inequalities in childhood obesity.

Growth patterns from birth to overweight at age 5-6 years of children with various backgrounds in socioeconomic status and country of origin: the ABCD study

INTRODUCTION

Children from minority groups are at increased risk of overweight. This study compared BMI growth patterns from birth onwards of boys and girls with overweight at 5-6 years, according to socioeconomic status (SES) and country of origin, in order to gain more insight into the critical periods of growth to overweight.

METHODS

A total of 3714 singletons of the multi-ethnic ABCD study were included. Within children with overweight at age 5-6 years (N = 487, prevalence boys: 11.6%, girls: 14.6%), BMI growth patterns from birth onwards (12.8 serial measurements; SD = 3.1) were compared between children from European (69.4%) and non-European mothers (30.6%), and between children from low (20.8%), mid (37.0%) or high SES (42.2%), based on maternal educational level.

RESULTS

BMI growth to overweight did not differ between children of European or non-European mothers, but it did differ according to maternal SES. Children with overweight in the low and mid SES group had a lower BMI in the first 2 years of life, an earlier adiposity rebound and increased in BMI more rapidly after age 2, resulting in a higher BMI at age 7 years compared to children with overweight in the high SES group [∆BMI (kg/m2 ) between high and low SES: boys 1.43(95%CI:0.16;3.01) and girls 1.91(0.55;3.27)].

CONCLUSION

Children with overweight from low SES have an early adiposity rebound and accelerated growth to a higher BMI at age 5-6 years compared to children with overweight from the high SES group. These results imply that timing of critical periods for overweight development is earlier in children with a low socioeconomic background as compared to other children.