Children’s Eating Behaviors and Energy Intake: Overlapping Influences and Opportunities for Intervention

Ciarán G. Forde, Anna Fogel, and Keri McCrickerd

Early-life factors combine to influence the development of childhood overweight/obesity [1], yet the eating behaviors that support a sustained positive energy balance and unhealthy growth outcomes are less clear. The transition from “risk” to childhood obesity operates largely through the emergence of maladaptive eating behaviors that consolidate during childhood, remain stable, and predict sustained higher energy intakes and adiposity [2]. We examined associations between eating behaviors, energy intake, and body composition among children from the GUSTO cohort (Growing Up in Singapore towards Healthy Outcomes). Measures were collected at 2 time points (4.5 and 6 years) and included premeal portion selection, within-meal coding of oral processing behaviors, and postmeal measures of food responsiveness, which were examined alongside measured parental feeding practices and parent reports of their child’s appetitive traits. 

Before lunch, children completed portion tasks on a computer, where they rated their appetite and then navigated through a series of food portion images to select their ideal portions of 8 familiar foods. Portions selected in the computer task significantly predicted the portions selected and consumed during a lunchtime meal. Children tended to pick more of foods they reported liking, but also smaller portions of foods they expected to be more filling, independently of whether they were liked. Importantly, the children who selected the largest portions tended to serve and consume a larger portion during the lunchtime meal. 

At the 4.5- and 6-year time points, behavioral coding was used to capture each bite, chew, and swallow during the lunch, to subsequently derive a series of oral processing behaviors associated with energy intake (Fig. 1). 

Children who ate at a faster rate (g/min) took larger bites, chewed less per bite, and consumed more energy at each meal (Fig. 2) [3, 4]. Faster eating rates at 4.5 years predicted faster eating and higher energy intakes at 6 years, with the same oral processing behaviors driving eating rates at both time points. Children who ate faster at 4.5 years also had higher adiposity at 6 years, emphasizing a role for these behaviors in prospective weight gain. Portion selection and eating rate independently predicted higher energy intakes, but children who chose the largest portions, had the longest meals, and ate at the fastest rates consumed the most energy, highlighting an important overlap in behaviors that contribute to higher energy intakes.


Fig. 1. Example of the behavioral coding scheme used to measure withinmeal bites, chews, and swallows to characterize oral processing behaviors of the children.

Postmeal child responsivity to palatable food cues was assessed using the EAH paradigm (eating in the absence of hunger), where children were given free access to snacks after they had eaten to fullness. Children who demonstrated EAH consumed more energy cumulatively from lunch and the snack test [5]. This EAH behavior was consistent over time and linked to faster eating rates, highlighting an overlap between behaviors that contribute to higher energy intakes both within and outside the main meals. 

Importantly, parents appear to be aware of their child’s appetitive traits, with faster eating and greater intake significantly correlated with higher “food responsiveness” and “enjoyment of food” reported by the parents in the CEBQ (Child Eating Behavior Questionnaire) [6]. Some parents responded to their child’s behaviors during the meal by using feeding practices more frequently during the meal, particularly among girls. Despite this, children who were prompted more continued to eat quickly and consume more energy [7]. Our findings suggest a bidirectional relationship between parental feeding practices, child eating behaviors, and subsequent weight status.


Fig. 2. Association between eating rate and energy intake during lunch (r2 = 0.38; p < 0·001; n = 386, adapted from Fogel et al. [3]).

Taken together, these findings highlight that higher energy intakes were consistently associated with a series of overlapping eating behaviors and parental feeding practices that were stable over time and most commonly found in children with highest BMIz scores. Our findings emphasize the need to go beyond targeting individual eating behaviors to consider the cumulative impact differences in energy selection, consumption, and associated parental feeding practices have on energy intake when developing interventions targeting children at risk of overweight or obesity.


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