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Growth Estimation of Under-Five Children Using Statistical Models in Central Region of India

Pradyuman Verma1, Jang Bahadur Prasad1, Noel George1

  • 1Department of Epidemiology and Biostatistics, KLE Academy of Higher Education & Research, Belgaum, 590010, Karnataka, India.

Diabetes & Metabolic Syndrome
|March 25, 2022
PubMed

Insights

This study evaluated statistical models for child growth estimation in Indian children under five. The Cubic and Power models best estimated height and weight, considering birth weight categories and socio-demographic factors.

Area of Science:

  • Pediatric Growth Monitoring
  • Biostatistics
  • Public Health Nutrition

Background:

  • Child growth estimation is crucial for monitoring health and development.
  • Understanding growth patterns in relation to birth weight is vital for early interventions.
  • Socio-demographic factors significantly influence child growth trajectories.

Purpose of the Study:

  • To assess the suitability of 11 statistical models for estimating child growth in under-five children.
  • To generate estimated growth curves for mean height and mean weight based on birth-weight categories.
  • To analyze growth patterns in the Central Region of India.

Main Methods:

  • Utilized National Family Health Survey-4 (NFHS-4) data from India (n=75,645).
  • Categorized under-five children into four birth-weight groups (<2000g, 2000-2499g, 2500-2999g, 3000+g).
  • Estimated growth curves for mean height and mean weight by sex and birth-weight category using selected statistical models.

Main Results:

  • Identified significant associations between child growth and seven socio-demographic factors (age, sex, birth order, BMI, mother's education, residence, wealth index).
  • The Cubic Model and Power Model demonstrated the best fit for height and weight data across different birth-weight categories.
  • Mean height and weight estimates with 95% Confidence Intervals were generated for boys and girls separately.

Conclusions:

  • Seven socio-demographic factors were significantly linked to birth weight.
  • Cubic and Power models are highly suitable for estimating child growth (mean height and weight) in relation to birth-weight categories for both sexes.
  • The findings provide valuable data for child health monitoring and interventions in India.
Abstract

Keywords:
Birth-weightChild-growthGrowth-curvesStatistical modelsUnder-5 children

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