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Updated: Aug 2, 2025
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Understanding Accelerated Summer Body Mass Index Gain by Tracking Changes in Children's Height, Weight, and Body Mass
R Glenn Weaver1, James W White1, Olivia Finnegan1
1Arnold School of Public Health, Department of Exercise Science, University of South Carolina, Columbia, South Carolina, USA.
Insights
Children
Area of Science:
- Pediatric endocrinology and metabolism
- Childhood obesity research
- Growth and development studies
Background:
- Childhood body mass index (BMI) gain during summer is a significant public health concern.
- Existing hypotheses, including the Circadian and Circannual Rhythm Model (CCRM) and the Structured Days Hypothesis (SDH), offer competing explanations for seasonal BMI changes.
- Understanding the underlying mechanisms is crucial for developing effective prevention strategies.
Purpose of the Study:
- To investigate the drivers of seasonal BMI gain in children.
- To differentiate between the CCRM and SDH in explaining children's summer BMI acceleration.
- To identify behavioral factors associated with changes in BMI z-score (zBMI).
Main Methods:
- Longitudinal study involving 147 children (mean age 8.2 years) with monthly height and weight measurements during the school year and one measurement in summer.
- Calculation of BMI z-score (zBMI) using CDC growth charts.
- Mixed-methods regression analysis to assess changes in height (%HΔ), weight (%WΔ), and zBMI during school breaks and summer vacation compared to regular school periods.
Main Results:
- Children exhibited accelerated weight gain (%WΔ) and zBMI during summer vacation and school breaks compared to regular school months.
- Height gain (%HΔ) remained relatively constant across different periods, suggesting weight gain is the primary driver of BMI changes.
- Seasonal analyses indicated the highest %WΔ and zBMI change occurred in summer, with potential links to fluctuations in sleep timing and screen time.
Conclusions:
- Findings provide evidence supporting both the CCRM and SDH, but the SDH appears to offer a more comprehensive explanation for children's summer BMI gain.
- Reduced structure and potential behavioral changes during breaks from school are key factors.
- Interventions focusing on consistent sleep patterns and reduced screen time, particularly during school breaks, are recommended to mitigate childhood BMI acceleration.
Abstract:
Drivers of summer body mass index (BMI) gain in children remain unclear. The Circadian and Circannual Rhythm Model (CCRM) posits summer BMI gain is biologically driven, while the Structured Days Hypothesis (SDH) proposes it is driven by reduced structure. Identify the mechanisms driving children's seasonal BMI gain through the CCRM and SDH. Children's (N = 147, mean age = 8.2 years) height and weight were measured monthly during the school year, and once in summer (July-August). BMI z-score (zBMI) was calculated using CDC growth charts. Behaviors were measured once per season. Mixed methods regression estimated monthly percent change in children's height (%HΔ), weight (%WΔ), and monthly zBMI for school year vs. summer vacation, seasonally, and during school months with no breaks vs. school months with a break ≥1 week. School year vs. summer vacation analyses showed accelerations in children's %WΔ (Δ = 0.9, Standard Error (SE) = 0.1 vs. Δ = 1.4, SE = 0.1) and zBMI (Δ = -0.01, SE = 0.01 vs. Δ = 0.04, SE = 0.3) during summer vacation, but %HΔ remained relatively constant during summer vacation compared with school (Δ = 0.3, SE = 0.0 vs. Δ = 0.4, SE = 0.1). Seasonal analyses showed summer had the greatest %WΔ (Δ = 1.8, SE = 0.4) and zBMI change (Δ = 0.05, SE = 0.03) while %HΔ was relatively constant across seasons. Compared with school months without a break, months with a break showed higher %WΔ (Δ = 0.7, SE = 0.1 vs. Δ = 1.6, SE = 0.2) and zBMI change (Δ = -0.03, SE = 0.01 vs. Δ = 0.04, SE = 0.01), but %HΔ was constant (Δ = 0.4, SE = 0.0 vs. Δ = 0.3, SE = 0.1). Fluctuations in sleep timing and screen time may explain these changes. Evidence for both the CCRM and SDH was identified but the SDH may more fully explain BMI gain. Interventions targeting consistent sleep and reduced screen time during breaks from school may be warranted no matter the season.
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