A total of 25.7 million children in the United States are classified as overweight or obese. Obesity is associated with deficits in executive function, which may contribute to poor dietary ...decision-making. Less is known about the associations between being overweight or obese and brain development.
To examine whether body mass index (BMI) is associated with thickness of the cerebral cortex and whether cortical thickness mediates the association between BMI and executive function in children.
In this cross-sectional study, cortical thickness maps were derived from T1-weighted structural magnetic resonance images of a large, diverse sample of 9 and 10-year-old children from 21 US sites. List sorting, flanker, matrix reasoning, and Wisconsin card sorting tasks were used to assess executive function.
A 10-fold nested cross-validation general linear model was used to assess mean cortical thickness from BMI across cortical brain regions. Associations between BMI and executive function were explored with Pearson partial correlations. Mediation analysis examined whether mean prefrontal cortex thickness mediated the association between BMI and executive function.
Among 3190 individuals (mean SD age, 10.0 0.61 years; 1627 51.0% male), those with higher BMI exhibited lower cortical thickness. Eighteen cortical regions were significantly inversely associated with BMI. The greatest correlations were observed in the prefrontal cortex. The BMI was inversely correlated with dimensional card sorting (r = -0.088, P < .001), list sorting (r = -0.061, P < .003), and matrix reasoning (r = -0.095, P < .001) but not the flanker task. Mean prefrontal cortex thickness mediated the association between BMI and list sorting (mean SE indirect effect, 0.014 0.008; 95% CI, 0.001-0.031) but not the matrix reasoning or card sorting task.
These results suggest that BMI is associated with prefrontal cortex development and diminished executive functions, such as working memory.
Attention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits, including poor working memory and difficulty inhibiting undesirable behaviors that cause academic and ...behavioral problems in children. Prior work has attempted to determine how these differences are instantiated in the structure and function of the brain, but much of that work has been done in small samples, focused on older adolescents or adults, and used statistical approaches that were not robust to model overfitting. The current study used cross-validated elastic net regression to predict a continuous measure of ADHD symptomatology using brain morphometry and activation during tasks of working memory, inhibitory control, and reward processing, with separate models for each MRI measure. The best model using activation during the working memory task to predict ADHD symptomatology had an out-of-sample R
= 2% and was robust to residualizing the effects of age, sex, race, parental income and education, handedness, pubertal status, and internalizing symptoms from ADHD symptomatology. This model used reduced activation in task positive regions and reduced deactivation in task negative regions to predict ADHD symptomatology. The best model with morphometry alone predicted ADHD symptomatology with an R
= 1% but this effect dissipated when including covariates. The inhibitory control and reward tasks did not yield generalizable models. In summary, these analyses show, with a large and well-characterized sample, that the brain correlates of ADHD symptomatology are modest in effect size and captured best by brain morphometry and activation during a working memory task.
•BMI was associated with widespread structural differences in cortical thickness, surface area, subcortical gray matter volumes and in white matter estimates of fractional anisotropy and mean ...diffusivity.•BMI was also associated with altered resting-state functional connectivity and working memory during an EN-back task but, contrary to some extant findings, was not related to reward or inhibitory control (as assessed by the Monetary Incentive Delay task and Stop Signal Task).•Excessive weight gain (i.e., more than 20 pounds in a year) was associated at baseline with thicker cortices, and differences in surface area and white matter in regions associated with attention and appetite control (e.g., insula, parahippocampal gyrus), but no functional associations were observed.•All analyses quantified generalizability to an unseen test set.•These findings suggest that brain structure, resting state and working memory are associated with current weight and that brain structure may have potential as an MRI biomarker to identify children at risk for pathological weight gain.
Multimodal neuroimaging assessments were utilized to identify generalizable brain correlates of current body mass index (BMI) and predictors of pathological weight gain (i.e., beyond normative development) one year later. Multimodal data from children enrolled in the Adolescent Brain Cognitive Development Study® at 9-to-10-years-old, consisted of structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), resting state (rs), and three task-based functional (f) MRI scans assessing reward processing, inhibitory control, and working memory. Cross-validated elastic-net regression revealed widespread structural associations with BMI (e.g., cortical thickness, surface area, subcortical volume, and DTI), which explained 35% of the variance in the training set and generalized well to the test set (R2 = 0.27). Widespread rsfMRI inter- and intra-network correlations were related to BMI (R2train = 0.21; R2test = 0.14), as were regional activations on the working memory task (R2train = 0.20; (R2test = 0.16). However, reward and inhibitory control tasks were unrelated to BMI. Further, pathological weight gain was predicted by structural features (Area Under the Curve (AUC)train = 0.83; AUCtest = 0.83, p < 0.001), but not by fMRI nor rsfMRI. These results establish generalizable brain correlates of current weight and future pathological weight gain. These results also suggest that sMRI may have particular value for identifying children at risk for pathological weight gain.
Environmental resources are related to childhood obesity risk and altered brain development, but whether these relationships are stable or if they have sustained impact is unknown. Here, we utilized ...a multidimensional index of childhood neighborhood conditions to compare the influence of various social and environmental disparities (SED) on body mass index (BMI)-brain relationships over a 2-year period in early adolescence.
Data were gathered the Adolescent Brain Cognitive Development Study
(
= 2,970, 49.8% female, 69.1% White, no siblings). Structure magnetic resonance imaging (sMRI), anthropometrics, and demographic information were collected at baseline (9/10-years-old) and the 2-year-follow-up (11/12-years-old). Region of interest (ROIs; 68 cortical, 18 subcortical) estimates of cortical thickness and subcortical volume were extracted from sMRI T
w images using the Desikan atlas. Residential addresses at baseline were used to obtain geocoded estimates of SEDs from 3 domains of childhood opportunity index (COI): healthy environment (COI
), social/economic (COI
), and education (COI
). Nested, random-effects mixed models were conducted to evaluate relationships of BMI with (1) ROI
COI
and (2) ROI
COI
Time. Models controlled for sex, race, ethnicity, puberty, and the other two COI domains of non-interest, allowing us to estimate the unique variance explained by each domain and its interaction with ROI and time.
Youth living in areas with lower COI
and COI
scores were heavier at the 2-year follow-up than baseline and exhibited greater thinning in the bilateral occipital cortex between visits. Lower COI
scores corresponded with larger volume of the bilateral caudate and greater BMI at the 2-year follow-up. COI
scores showed the greatest associations (
= 20 ROIs) with brain-BMI relationships: youth living in areas with lower COI
had thinner cortices in prefrontal regions and larger volumes of the left pallidum and Ventral DC. Time did not moderate the COI
x ROI interaction for any brain region during the examined 2-year period. Findings were independent of family income (i.e., income-to-needs).
Collectively our findings demonstrate that neighborhood SEDs for health-promoting resources play a particularly important role in moderating relationships between brain and BMI in early adolescence regardless of family-level financial resources.
Decision-making contributes to what and how much we consume, and deficits in decision-making have been associated with increased weight status in children. Nevertheless, the relationships between ...cognitive and affective processes underlying decision-making (i.e., decision-making processes) and laboratory food intake are unclear. We used data from a four-session, within-subjects laboratory study to investigate the relationships between decision-making processes, food intake, and weight status in 70 children 7-to-11-years-old. Decision-making was assessed with the Hungry Donkey Task (HDT), a child-friendly task where children make selections with unknown reward outcomes. Food intake was measured with three paradigms: (1) a standard
ad libitum
meal, (2) an eating in the absence of hunger (EAH) protocol, and (3) a palatable buffet meal. Individual differences related to decision-making processes during the HDT were quantified with a reinforcement learning model. Path analyses were used to test whether decision-making processes that contribute to children’s (a) expected value of a choice and (b) tendency to perseverate (i.e., repeatedly make the same choice) were indirectly associated with weight status through their effects on intake (kcal). Results revealed that increases in the tendency to perseverate after a gain outcome were positively associated with intake at all three paradigms and indirectly associated with higher weight status through intake at both the standard and buffet meals. Increases in the tendency to perseverate after a loss outcome were positively associated with EAH, but only in children whose tendency to perseverate persistedacross trials. Results suggest that decision-making processes that shape children’s tendencies to repeat a behavior (i.e., perseverate) are related to laboratory energy intake across multiple eating paradigms. Children who are more likely to repeat a choice after a positive outcome have a tendency to eat more at laboratory meals. If this generalizes to contexts outside the laboratory, these children may be susceptible to obesity. By using a reinforcement learning model not previously applied to the study of eating behaviors, this study elucidated potential determinants of excess energy intake in children, which may be useful for the development of childhood obesity interventions.
Longer exclusive breastfeeding duration has been associated with differences in neural development, better satiety responsiveness, and decreased risk for childhood obesity. Given hippocampus ...sensitivity to diet and potential role in the integration of satiety signals, hippocampus may play a role in these relationships. We conducted a secondary analysis of 149, 7–11‐year‐olds (73 males) who participated in one of five studies that assessed neural responses to food cues. Hippocampal grey matter volume was extracted from structural scans using CAT12, weight status was assessed using age‐ and sex‐adjusted body mass index (%BMIp85), and parents reported exclusive breastfeeding duration and satiety responsiveness (Children's Eating Behaviour Questionnaire). Separate path models for left and right hippocampus tested: (1) the direct effect of exclusive breastfeeding on satiety responsiveness and its indirect effect through hippocampal grey matter volume; (2) the direct effect of hippocampal grey matter volume on %BMIp85 and its indirect effect through satiety responsiveness. %BMIp85 was adjusted for maternal education, yearly income, and premature birth while hippocampal grey matter volume was adjusted for total intercranial volume, age, and study from which data were extracted. Longer exclusive breastfeeding duration was associated with greater bilateral hippocampal grey matter volumes. In addition, better satiety responsiveness and greater left hippocampal grey matter volume were both associated with lower %BMIp85. However, hippocampal grey matter volumes were not associated with satiety responsiveness. Although no relationship was found between breastfeeding and child weight status, these results highlight the potential impact of exclusive breastfeeding duration on the hippocampal structure.
Given that hippocampus is sensitive to diet, it may play a role in the associations between longer exclusive breastfeeding duration, better satiety responsiveness, and decreased risk for childhood obesity. Longer exclusive breastfeeding duration was associated with greater bilateral hippocampal grey matter volumes. While breastfeeding duration was not associated with child weight status, better satiety responsiveness and greater left hippocampal grey matter volume were both associated with lower weight status. These results highlight the potential impact of exclusive breastfeeding duration on the hippocampal structure.
Key messages
Longer exclusive breastfeeding was associated with greater bilateral hippocampal grey matter volume but not satiety responsiveness in children.
While exclusive breastfeeding duration was not directly associated with weight status, better satiety responsiveness and greater left hippocampal grey matter volume were both associated with lower weight status in children.
This study highlights the potential impact of exclusive breastfeeding on hippocampal structure, providing a possible mechanism in which breastfeeding may reduce the risk for excess childhood weight gain.
Future studies need to determine the relative impact that complementary periods of breastfeeding may have on regional brain development and satiety responsiveness.
Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data ...from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings.
Articles published from 2017 to 2023 that used ABCD Study data were reviewed using more than 30 data extraction items to gather information on data use practices. Total frequencies were reported for each extraction item, along with computation of a Level of Completeness (LOC) score that represented overall endorsement of extraction items. Univariate linear regression models were used to examine the correlation between LOC scores and individual extraction items. Post hoc analysis included examination of whether LOC scores were correlated with the logged 2-year journal impact factor.
There were 549 full-length articles included in the main analysis. Analytic scripts were shared in 30% of full-length articles. The number of participants excluded due to missing data was reported in 60% of articles, and information on missing data for individual variables (e.g., household income) was provided in 38% of articles. A table describing the analytic sample was included in 83% of articles. A race and/or ethnicity variable was included in 78% of reviewed articles, while its inclusion was justified in only 41% of these articles. LOC scores were highly correlated with extraction items related to examination of missing data. A bottom 10% of LOC score was significantly correlated with a lower logged journal impact factor when compared to the top 10% of LOC scores (β=-0.77, 95% -1.02, -0.51; p-value < 0.0001).
These findings highlight opportunities for improvement in future papers using ABCD Study data to readily adapt analytic practices for better transparency and reproducibility efforts. A list of recommendations is provided to facilitate adherence in future research.
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