Complementary and alternative metrics for tracking population-level trends in child linear growth

Area of Science:

• Global Health
• Nutrition Science
• Anthropometry

Background:

• Stunting prevalence is a key indicator for child nutritional status in low- and middle-income countries (LMICs).
• Alternative and complementary metrics to stunting may offer broader insights into linear growth faltering.
• Existing anthropometric data offer potential for developing novel growth metrics.

Purpose of the Study:

• To identify and evaluate alternative and complementary linear growth metrics to stunting prevalence.
• To assess the correlation of various anthropometric metrics with stunting and population indicators.
• To determine the utility of novel metrics in tracking child health and nutrition in LMICs.

Main Methods:

• Utilized data from 156 Demographic and Health Surveys in 63 LMICs (2000-2020).
• Generated and analyzed multiple linear growth metrics, including measures of height distribution and model-derived indicators (e.g., HAZ, HAD, GD, SITAR-IP).
• Employed Spearman's rank correlation to compare metrics against stunting and population indicators (mortality, GDP, maternal education).

Main Results:

• Identified 6 metrics as potential alternatives to stunting (e.g., stunting 2-5y, mean HAZ <5y and 2-5y).
• Identified 6 metrics as complementary to stunting (e.g., SITAR-IP, HAZ slope 1m-2y).
• Found three metrics (HAZ slope 2-5y, HAD slope 2-5y, predicted HAZ at birth) showed weak correlations with population indicators.

Conclusions:

• Several linear growth metrics can effectively substitute or supplement stunting prevalence.
• These alternative and complementary metrics enhance the tracking of global child health and nutrition.
• Further research is recommended to explore the practical application of these metrics.