Trajectories of child undernutrition in Ethiopia: a multivariate GEE approach.

BACKGROUND AND OBJECTIVES: Child undernutrition remains a significant public health issue in Ethiopia despite Millennium Development Goal efforts. Most prior Ethiopian studies have relied on cross-sectional designs or have modelled underweight, stunting and wasting as separate independent outcomes, limiting insight into their longitudinal interplay. This study employs a multivariate longitudinal framework to jointly examine trajectories, co-occurrence and shared determinants of all three anthropometric outcomes from infancy through adolescence. METHODS: We utilised the Young Lives Cohort Survey (YLCS), collecting data from ~1997 Ethiopian children across five time points (2002-2016). A multivariate generalised estimating equations (GEE) model with a logit link function and exchangeable working correlation structure assessed associations between covariates and three undernutrition outcomes (underweight, stunting and wasting) defined by WHO z-scores (<-2 SD=undernutrition; ≥-2 SD=normal). Covariate effects were estimated with ORs and 95% CIs. RESULTS: Undernutrition prevalence varied over time: underweight peaked at 52.1% at age 12, stunting was highest at 42.5% at age 1 (persisting at 25.6% by age 15), and wasting reached 41.2% at age 12. Overall, 37.2% of measurements showed underweight, 30.2% stunting and 24.7% wasting. The GEE model showed that higher wealth was associated with lower odds of underweight (OR=0.05, 95% CI: 0.02 to 0.11), stunting (OR=0.20, 95% CI 0.10 to 0.38) and wasting (OR=0.17, 95% CI 0.07 to 0.41). Females had lower odds (eg, underweight OR=0.61, 95% CI 0.53 to 0.70), while lack of safe water was associated with higher wasting odds (OR=1.40, 95% CI 1.16 to 1.69). Wasting odds surged by age 12 (OR=3.65, 95% CI 3.19 to 4.19). CONCLUSION: Undernutrition burden shifted across childhood, with stunting predominating in early years, underweight peaking in preadolescence and wasting escalating in later childhood. Wealth-targeted economic support programmes, poverty reduction strategies and improved water purification may help to address these disparities.