Related Experiment Video
Updated: Jun 9, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
Detecting Age Prone to Growth Retardation in Children Through a Bi-Response Nonparametric Regression Model with a
Anna Islamiyati1, Anisa Kalondeng1, Muhammad Zakir2
1Department of Statistics, Hasanuddin University, Makassar, Indonesia.
Insights
Identifying vulnerable growth periods in early childhood is crucial. Boys show growth slowdown from age 2, while girls experience it from age 3, impacting long-term development.
Area of Science:
- Pediatrics
- Child Development
- Growth Monitoring
Background:
- Child growth and development from 0-60 months significantly influences long-term health outcomes.
- Growth retardation during early childhood can have lasting effects.
- Identifying specific age vulnerabilities is key for timely intervention.
Purpose of the Study:
- To pinpoint critical age windows for growth retardation in boys and girls aged 0-60 months.
- To analyze sex-specific patterns of slowed growth in early childhood.
- To provide data for targeted growth monitoring strategies.
Main Methods:
- Cross-sectional study design utilizing measurement data from 698 children (369 boys, 329 girls).
- Data collected from weighing at Health Integrated Service Posts in South Sulawesi Province, 2022.
- Nonparametric bi-response regression model with penalized splines (knots at 12, 24, 36, 48 months) was employed.
Main Results:
- Penalized spline regression coefficients indicated slowed growth outside normal limits.
- Boys exhibited minimal weight and height increases between 12-24 months (approx. 0.3 kg, 0.3 cm).
- Girls showed limited weight and height gains between 24-36 months (approx. 0.6 kg, 1 cm).
Conclusions:
- Boys experience a significant growth slowdown starting at 2 years old, persisting until age 5.
- Girls' growth rate decelerates from age 3 through age 5.
- These findings highlight distinct sex-specific vulnerable periods for growth retardation in early childhood.
Background:
The growth of children aged 0-60 months can impact their subsequent growth and development. This study aims to identify the vulnerable age for boys and girls, who experience growth retardation within this age range.
Methods:
The study design used was a cross-sectional approach in which each child's measurement data was only taken once. The data were obtained from weighing results at the Health Integrated Service Post in South Sulawesi Province in 2022. The number of data analyzed was 698 children, namely 369 boys and 329 girls by considering the factors of age, weight, and height. We used a nonparametric bi-response regression model estimated using a penalized spline. The knots used are 12, 24, 36, and 48 on each model.
Results:
The value of the penalized spline regression coefficient in the model indicates that the child's growth is slowed down and is not within normal limits. This can be seen in the weight and height of boys from the age of reaching 12 months to 24 months, only increasing by about 0.3 kg and 0.3 cm. For girls, the problem occurs from the age of 24 to 36 months, namely their weight increases by about 0.6 kg, and their height increases by about 1 cm.
Conclusions:
The analysis results show that boys' growth slows down at 2 years of age and continues until 5 years of age. In the case of girls, their growth begins to slow when they are 3 years old until they reach 5 years old.
Related Concept Videos
Residuals and Least-Squares Property
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Survival Tree
Building a Survival Tree
Constructing a...
Mechanistic Models: Compartment Models in Individual and Population Analysis
Outliers and Influential Points
Two-Way ANOVA
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...

