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Concept of Trajectory Modelling - Associations of early childhood
body mass index trajectories with body composition and
cardiometabolic markers at age 10 years: the Ethiopian infant
anthropometry and body composition (iABC) birth cohort study
University of Copenhagen
Jimma University, Ethiopia

The Global Health Problem of Childhood Overweight
Childhood overweight is a major global health problem (37 million Under 5)
- key risk factor for cardiovascular disease and type 2 diabetes in adulthood.
- In high-income countries, accelerated BMI growth in early childhood has
been linked with overweight and higher cardiometabolic (CM) risk later in
life.
-In middle-income countries, rapid weight and BMI gain in infancy and
childhood have been associated with greater lean mass ( ) rather than
fat mass in childhood and adulthood.

Importance of Understanding BMI Growth Patterns
Early BMI growth trajectories better predicted later body composition and
risk of obesity in childhood than a single-point time BMI.
How early BMI associated with body composition, adiposity, and
cardiometabolic risk track in later childhood in LMICs - to identify those at
risk and provide timely interventions.

Aim & hypotheses
Previous Findings:
- Identified 4 distinct BMI growth patterns in Ethiopian iABC birth cohort from ages 0 to 5.
- High early BMI growth linked to larger body size, higher FFM and FM, and triglycerides.
Current Study Aim: Examine associations of BMI growth patterns with age 10 body measurements,
composition, abdominal fat, and disease markers.
Hypotheses:
- Rapid BMI growth may lead to higher FM and markers related to lipid metabolism at age 10.
- Slow BMI growth may result in lower FFM, body fat levels, and markers related to lipid metabolism
at age 10.

Covariates
Child anthropometry – 1.5, 2.5, 3.5, 4.5 , 6 mo & 1, 1.5, 2,3,4,5, 10 yrs.
Sociodemographic Characteristics: Information obtained within 48 hours after delivery,
including maternal age, highest educational status, and family wealth status.
Child Gestational Age: Calculated using the Ballard score.
Family Economic Status: Assessed using Wealth Index.
Maternal Anthropometric Measurements: Height, weight
Breastfeeding Status: Assessed between 4 and 6 months (EBF/predominant/Partial/Not
breastfed)

Study Design and Participant Selection
- iABC birth cohort established in December 2008 in Jimma town, Ethiopia.
- Mothers giving birth in the maternity ward of Jimma University Specialized
Hospital, and their newborns recruited within 48 hours after birth.
- Eligibility: living in Jimma town, healthy and term newborn (≥37 weeks of
gestation) with a weight of ≥1,500 g, and without any medical complications
and congenital malformations.
- From 0-5 years of age, the children were invited for a total of 12 visits.

Follow-up and Data Collection
Follow-up visit conducted from June 2019 to December 2020, when children
were 7-12 years old.
Data collection procedures included overnight fast.

Statistical Analyses
Outcomes studied at the 10-year follow-up included anthropometric
measurements, body composition, abdominal fat, and cardiometabolic
markers.
Associations between categorical exposure variables (latent BMI trajectories
from 0-5 years) and the continuous outcomes at 10 years, analyzed using
multiple linear regression.

Latent Class Trajectory Modeling (LCTM)

One size fits all
Growth Parameters: These are the intercept (initial status) and
slopes (change per unit of time) that describe growth in a sample.
Assumptions: The model assumes a certain distribution of
variance around these growth parameters, typically a normal
distribution.
Adjusted Predictions with 95% CIs

Latent classes
Intercept
Slope
Var 1 Var 2 Var 3 Var 4
Time 0 Time 1 Time 2 Time 3

Concept of Trajectory Modelling using the study

- Regression analyses were performed as complete case analyses (children with complete
data on all covariates).
- Multiple imputations were performed to impute missing data for children who attended the
10-year follow-up.

Model Adjustments
Model 1 Child’s sex, exact age at the 10-year follow-up visit
Model 2
Model 1 + child’s birth order, gestational age at birth, maternal age
at delivery, maternal height, maternal highest educational status,
family socioeconomic status (wealth index)
Model 3 Model 2 + birth weight
Model 4 Model 3 + current body size measurements

Key Findings
slow and rapid growth to high BMI trajectory had greater waist circumference and
FMI.
slow growth to high BMI had greater abdominal subcutaneous fat.
stable low BMI had lower FFMI at 10 years of age.
slow growth to high BMI trajectory had higher insulin and HOMA-IR.
rapid growth to high BMI had higher C-peptide concentration.
rapid growth to high BMI had lower total cholesterol concentration at 10 years.

Limitations of the Study
High loss to follow up
unmeasured exposures that can affect growth and body composition (between 5 and 10 yrs)
Breastfeeding not included in the model (? Literature)
No causal-effect associations.
Those who did not attend 10 yr follow up are much healthier (bias?)
Not representative of the general population - healthy and term children from a tertiary centre.

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Concept of Trajectory Modelling using the study

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