Abstract
Recent research has shown that the pattern of change over time, or trajectory, of body mass index (BMI) varies among children. However, the factors that underlie the heterogeneity in these trajectories remain largely unexplored. Our aim was to use a growth mixture model to empirically identify classes of BMI trajectories (from birth to 11.5 years) and examine the effects of breastfeeding, introduction of solids, as well as food and nutrient intake at 18 months on these BMI trajectories. We identified three BMI growth trajectories between birth and age 11.5 years, separately in boys and girls. Breastfeeding duration less than six months and the early introduction of solids did not adversely influence BMI trajectories in our sample but high intakes of meat, particularly high fat varieties, and high intakes of carbohydrate at age around 18 months were associated with a high BMI trajectory in boys. It is not clear whether these dietary factors confer a direct risk of higher BMI in childhood or are markers for other dietary patterns that are present early and/or develop through childhood and contribute to higher BMI.
Highlights
Recent research has shown that the pattern of change over time, or trajectory, of body mass index (BMI) varies among children [1,2,3,4,5,6]
Complete data were available for all 370 subjects for breastfeeding and introduction to solids, and 18-month dietary data were available for 298 (81%) subjects
We found no relationship between BMI trajectory class and breastfeeding or early introduction of solids (Table 3)
Summary
Recent research has shown that the pattern of change over time, or trajectory, of body mass index (BMI) varies among children [1,2,3,4,5,6]. Statistical models for tracking BMI and weight status changes over time have utilized growth mixture modeling, a method that defines distinct groups, often called classes, within a sample based on their response patterns over time. Members of the same group (class) share a similar pattern of change over time. Individuals are assigned to the class for which they have the highest probability of membership. The advantage of growth mixture modeling over traditional analyses of changes in weight over time using random effects models is that, unlike the latter, the former does not require an assumption that all members of the sample come from the same underlying distribution.
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