Insight into the resilience of local food systems—variability driven by climate, conflict, and food price shocks—is critical for the treatment and prevention of child acute malnutrition.
We use a combination of latent class mixed modeling and time-to-event analysis to develop and test a measure of resilience that is outcome-based, sensitive to specific shocks and stressors, and captures the enduring effects of how frequently and severely children face the risk of acute malnutrition.
Harnessing a high-resolution longitudinal dataset with anthropometric information on 5,597 Kenyan households for the 2016–20 period, we identify resilience trajectories for 141 wards across Kenya. These trajectories—characterized by variation in the duration and severity of episodes of acute malnutrition—are associated with differential risk: (1) some 57% of wards exhibit an increasing trajectory—high household risk despite growing resilience; (2) 39% exhibit chronic characteristics—showing no real signs of recovery after an episode of crisis; (3) 3% exhibit robust characteristics—low variability with low-levels of individual household risk; whereas (4) 1% show a steady decrease in resilience—associated with high levels household risk.
Our findings highlight the importance of measuring resilience at the ward-level in order to better understand variation in the nutritional status of rural households.