Background: Healthcare monitoring of child growth reduces with age, which may increase parental influences on children’s weight development. This study aimed to examine the association between maternal underestimation of child’s weight at age 5/6 and weight development between 5 and 12 years. Methods: We performed univariate and multivariate linear regression analyses with data on maternal perception of child’s weight and weight development (∆SDS body-mass index; BMI) derived from the Amsterdam Born Children and their Development (ABCD) birth-cohort study. Underestimation was defined by comparing maternal perception of child’s weight with the actual weight status of her child. Associations were studied in two groups: children with overweight (n = 207) and children with normal weight (n = 1982) at baseline (children with underweight were excluded). Results: Underestimation was 5.5% in children with normal weight and 79.7% in children with overweight. Univariate analyses in children with normal weight and overweight showed higher weight development for children with underestimated vs. accurately estimated weights (respectively: β = 0.19, p < 0.01; β = 0.22, p < 0.05). After adjusting for child sex and baseline SDS BMI, the effect size became smaller for children with a normal weight (β = 0.15, p < 0.05) and overweight (β = 0.18, p > 0.05). Paternal and maternal BMI, ethnicity, and educational level explained the association further (remaining β = −0.11, p > 0.05 in children with normal weight; β = 0.06, p > 0.05 in children with overweight). Conclusions: The relationship between maternal underestimation of child’s weight and higher weight development indicates a need for promoting a realistic perception of child’s weight, this is also the case if the child has a normal weight.

Purpose To comprehend the complex relationship between symptoms and health-related quality of life (HRQoL) in patients with diffuse glioma, we applied symptom network analysis to identify patterns of associations between depression, cognition, brain tumor-related symptoms, and HRQoL. Additionally, we aimed to compare global strength between symptom networks to understand if symptoms are more tightly connected in different subgroups of patients. Methods We included 256 patients and stratified the sample based on disease status (preoperative vs. postoperative), tumor grade (grade II vs. III/IV), and fatigue status (non-fatigued vs. fatigued). For each subgroup of patients, we constructed a symptom network. In these six networks, each node represented a validated subscale of a questionnaire and an edge represented a partial correlation between two nodes. We statistically compared global strength between networks. Results Across the six networks, nodes were highly correlated: fatigue severity, depression, and social functioning in particular. We found no differences in GS between the networks based on disease characteristics. However, global strength was lower in the non-fatigued network compared to the fatigued network (5.51 vs. 7.49, p < 0.001). Conclusions Symptoms and HRQoL are highly interrelated in patients with glioma. Interestingly, nodes in the network of fatigued patients were more tightly connected compared to non-fatigued patients. Implications for Cancer Survivors We introduce symptom networks as a method to understand the multidimensionality of symptoms in glioma. We find a clear association between multiple symptoms and HRQoL, which underlines the need for integrative symptom management targeting fatigue in particular.