Increased Resting-State Functional Connectivity in Obese Adolescents; A Magnetoencephalographic Pilot Study

BACKGROUND: Obesity is not only associated with metabolic abnormalities, but also with cognitive dysfunction and changes in the central nervous system. The present pilot study was carried out to investigate functional connectivity in obese and non-obese adolescents using magnetoencephalography (MEG). METHODOLOGY/PRINCIPAL FINDINGS: Magnetoencephalographic recordings were performed in 11 obese (mean BMI 38.8+/-4.6 kg/m(2)) and 8 lean (mean BMI 21.0+/-1.5 kg/m(2)) female adolescents (age 12-19 years) during an eyes-closed resting-state condition. From these recordings, the synchronization likelihood (SL), a common method that estimates both linear and non-linear interdependencies between MEG signals, was calculated within and between brain regions, and within standard frequency bands (delta, theta, alpha1, alpha2, beta and gamma). The obese adolescents had increased synchronization in delta (0.5-4 Hz) and beta (13-30 Hz) frequency bands compared to lean controls (P(delta total) = 0.001; P(beta total) = 0.002). CONCLUSIONS/SIGNIFICANCE: This study identified increased resting-state functional connectivity in severe obese adolescents. Considering the importance of functional coupling between brain areas for cognitive functioning, the present findings strengthen the hypothesis that obesity may have a major impact on human brain function. The cause of the observed excessive synchronization is unknown, but might be related to disturbed motivational pathways, the recently demonstrated increase in white matter volume in obese subjects or altered metabolic processes like hyperinsulinemia. The question arises whether the changes in brain structure and communication are a dynamic process due to weight gain and whether these effects are reversible or not

Determinants of rapid weight gain during infancy: baseline results from the NOURISH randomised controlled trial

Background: Rapid weight gain in infancy is an important predictor of obesity in later childhood. Our aim was to determine which modifiable variables are associated with rapid weight gain in early life.Methods: Subjects were healthy infants enrolled in NOURISH, a randomised, controlled trial evaluating an intervention to promote positive early feeding practices. This analysis used the birth and baseline data for NOURISH. Birthweight was collected from hospital records and infants were also weighed at baseline assessment when they were aged 4-7 months and before randomisation. Infant feeding practices and demographic variables were collected from the mother using a self administered questionnaire. Rapid weight gain was defined as an increase in weight-for-age Z-score (using WHO standards) above 0.67 SD from birth to baseline assessment, which is interpreted clinically as crossing centile lines on a growth chart. Variables associated with rapid weight gain were evaluated using a multivariable logistic regression model.Results: Complete data were available for 612 infants (88% of the total sample recruited) with a mean (SD) age of 4.3 (1.0) months at baseline assessment. After adjusting for mother's age, smoking in pregnancy, BMI, and education and infant birthweight, age, gender and introduction of solid foods, the only two modifiable factors associated with rapid weight gain to attain statistical significance were formula feeding [OR = 1.72 (95%CI 1.01-2.94), P = 0.047] and feeding on schedule [OR = 2.29 (95%CI 1.14-4.61), P = 0.020]. Male gender and lower birthweight were non-modifiable factors associated with rapid weight gain.Conclusions: This analysis supports the contention that there is an association between formula feeding, feeding to schedule and weight gain in the first months of life. Mechanisms may include the actual content of formula milk (e.g. higher protein intake) or differences in feeding styles, such as feeding to schedule, which increase the risk of overfeeding.Trial Registration: Australian Clinical Trials Registry ACTRN12608000056392

Parent engagement and attendance in PEACH™ QLD: An up-scaled parent-led childhood obesity program

Background: Parenting, Eating and Activity for Child Health (PEACH™) is a multicomponent treatment program delivered over ten group sessions to parents of overweight/obese primary school-aged children. It has been shown to be efficacious in an RCT and was recently translated to a large-scale community intervention funded by the Queensland (Australia) Gover nment. Engagement (enrolment and attendance) was critical to achieving program outcomes and was challenging. The purpose of the present study was to examine sample characteristics and mediating factors that potentially influenced program attendance. Methods: Data collected from parents who attended at least one PEACH™ Queensland session delivered between October 2013 and October 2015 (47 programs implemented in 29 discrete sites), was used in preliminary descriptive analyses of sample characteristics and multilevel single linear regression analyses. Mediation analysis examined associations between socio-demographic and parent characteristics and attendance at group sessions and potential mediation by child and parent factors. Results: 365/467 (78%) enrolled families (92% mothers) including 411/519 (79%) children (55% girls, mean age 9 ± 2 years) attended at least one session (mean 5.6 ± 3.2). A majority of families (69%) self-referred to the program. Program attendance was greater in: advantaged (5.9 ± 3.1 sessions) vs disadvantaged families (5.4 ± 3.4 sessions) (p < 0.05); partnered (6.1 ± 3.1 sessions) vs un-partnered parents (5.0 ± 3.1 sessions) (p < 0.01); higher educated (6.1 ± 3.0 sessions) vs lower educated parents (5.1 ± 3.3 sessions) (p = 0.02); and self-referral (6.1 ± 3.1) vs professional referral (4.7 ± 3.3) (p < 0.001). Child (age, gender, pre-program healthy eating) and parent (perceptions of child weight, self-efficacy) factors did not mediate these relationships. Conclusions: To promote reach and effectiveness of up-scaled programs, it is important to identify ways to engage less advantaged families who carry higher child obesity risk. Understanding differences in referral source and parent readiness for change may assist in tailoring program content. The influence of program-level factors (e.g. facilitator and setting characteristics) should be investigated as possible alternative mediators to program engagement. © 2017 The Author(s)