# Food addiction in children: a network analysis of nutritional, metabolic, and sociodemographic factors

## TL;DR

This study explores how food addiction in children connects with factors like age, socioeconomic status, and metabolism using network analysis.

## Contribution

The study introduces a novel network analysis framework to evaluate food addiction's role in childhood, linking sociodemographic, nutritional, and metabolic variables.

## Key findings

- Food addiction showed moderate centrality in sociodemographic and metabolic networks, connecting key variables like age and socioeconomic class.
- In contrast, food addiction had a peripheral role in the anthropometric network with limited direct links and intermediation.

## Abstract

Food addiction (FA) is a condition in which ultra-processed foods (UPFs) activate the brain's reward pathways, leading to binge eating, loss of control, and continued consumption despite negative consequences. It can appear early in childhood and is linked to behavioral, sociodemographic, and metabolic factors. This study assessed the contribution of FA, its structure, and connectivity in relation to sociodemographic, nutritional status, and metabolic variables in network analysis.

A cross-sectional study was conducted with 93 children (7–11 years old) living in Vitória de Santo Antão, Brazil. FA was assessed using the Yale Food Addiction Scale for Children, which was translated and validated for the Brazilian child population. Sociodemographic (age, sex, race, socioeconomic class), anthropometric (body weight, height, waist circumference, BMI, BMI-for-age, body fat percentage, lean mass, and fat mass), and metabolic (blood pressure, total cholesterol, triglycerides, HDL, LDL, and fasting glucose) factors were analyzed. For network analysis, the degree centrality (DC), closeness centrality (CC), betweenness centrality (BC), and eigenvector centrality (EC) were evaluated.

FA exhibited moderate centrality in sociodemographic and metabolic networks, acting as a connector between key variables such as age and socioeconomic class (BC = 0.071–0.500; EC = 0.301–0.500; CC = 0.636–0.667). These metrics indicate that FA, while not dominant, maintains access to influential nodes and participates in relevant information pathways. In contrast, within the anthropometric network, FA showed a peripheral role, with fewer direct links (DC = 0.222–0.285) and limited intermediation (BC = 0.111).

Variation in centrality across domains underscores the selective integration of FA, suggesting that its impact is context dependent.

Food addiction involves the uncontrolled and impulsive consumption of ultra-processed foods and can occur in childhood. Several factors may be associated with this condition; therefore, this study evaluates the contribution of food addiction within a network analysis framework including sociodemographic, nutritional, and metabolic variables. This study was conducted in Vitória de Santo Antão, Brazil, with children aged 7 to 11 years. Three networks were constructed to analyze the association between food addiction and sociodemographic, anthropometric, and metabolic factors. Food addiction played a moderate role in the sociodemographic and metabolic networks, acting as a link between factors such as age and socioeconomic status. In contrast, in the anthropometric network, it had little influence, appearing more isolated and showing few direct connections with other variables.