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Updated: Mar 11, 2026
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Potential selection effects when estimating associations between the infancy peak or adiposity rebound and later body
C Börnhorst1, A Siani2, M Tornaritis3
1Biometry and Data Management, Leibniz Institute for Prevention Research and Epidemiology-BIPS, Bremen, Germany.
Insights
Excluding children with unidentifiable infancy peak (IP) and adiposity rebound (AR) can bias body mass index (BMI) growth studies. Children with faster BMI growth are often excluded, affecting results for later weight status prediction.
Area of Science:
- Pediatric obesity research
- Growth trajectory analysis
- Childhood health and development
Background:
- Infancy peak (IP) and adiposity rebound (AR) are critical periods for childhood BMI development.
- Estimating associations between BMI at IP/AR and later weight status is crucial for public health interventions.
- Exclusion criteria in studies may inadvertently introduce selection bias.
Purpose of the Study:
- To evaluate the selection effect of excluding children with non-identifiable IP and AR.
- To assess how this exclusion impacts the estimation of BMI trajectories and later weight status.
- To identify potential alternative predictors for later weight status.
Main Methods:
- Utilized fractional polynomial multilevel models on longitudinal data from 4744 children (0-8 years).
- Derived individual BMI trajectories and estimated age and BMI at IP and AR.
- Related BMI growth measures to later BMI z-scores in 9.2-year-old children.
Main Results:
- 5.4% (IP) and 7.8% (AR) of children had non-identifiable measures, showing higher BMI growth.
- Exclusion of these children demonstrated a significant selection effect.
- BMI at 1 and 5 years showed strong correlations with later BMI z-scores.
Conclusions:
- Excluding children with non-identifiable IP/AR can lead to selection bias in BMI growth studies.
- Higher BMI growth in infancy and childhood may preclude IP/AR identifiability.
- BMI at 1 and 5 years may serve as more robust predictors for long-term weight status.
Introduction:
This study aims to evaluate a potential selection effect caused by exclusion of children with non-identifiable infancy peak (IP) and adiposity rebound (AR) when estimating associations between age and body mass index (BMI) at IP and AR and later weight status.
Subjects And Methods:
In 4744 children with at least 4 repeated measurements of height and weight in the age interval from 0 to 8 years (37 998 measurements) participating in the IDEFICS (Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants)/I.Family cohort study, fractional polynomial multilevel models were used to derive individual BMI trajectories. Based on these trajectories, age and BMI at IP and AR, BMI values and growth velocities at selected ages as well as the area under the BMI curve were estimated. The BMI growth measures were standardized and related to later BMI z-scores (mean age at outcome assessment: 9.2 years).
Results:
Age and BMI at IP and AR were not identifiable in 5.4% and 7.8% of the children, respectively. These groups of children showed a significantly higher BMI growth during infancy and childhood. In the remaining sample, BMI at IP correlated almost perfectly (r⩾0.99) with BMI at ages 0.5, 1 and 1.5 years, whereas BMI at AR correlated perfectly with BMI at ages 4-6 years (r⩾0.98). In the total study group, BMI values in infancy and childhood were positively associated with later BMI z-scores where associations increased with age. Associations between BMI velocities and later BMI z-scores were largest at ages 5 and 6 years. Results differed for children with non-identifiable IP and AR, demonstrating a selection effect.
Conclusions:
IP and AR may not be estimable in children with higher-than-average BMI growth. Excluding these children from analyses may result in a selection bias that distorts effect estimates. BMI values at ages 1 and 5 years might be more appropriate to use as predictors for later weight status instead.
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