Abstract
Child acute malnutrition (AM) is an important cause of child mortality. Accurately estimating its burden requires cumulative incidence data from longitudinal studies, which are rarely available in low-income settings. In the absence of such data, the AM burden is approximated using prevalence estimates from cross-sectional surveys and the incidence correction factor $K$, obtained from the few available cohorts that measured AM. We estimated $K$ factors for severe acute malnutrition (SAM) and moderate acute malnutrition (MAM) from AM incidence and prevalence using representative cross-sectional baseline and longitudinal data from 2 cluster-randomized controlled trials (Innovative Approaches for the Prevention of Childhood Malnutrition—PROMIS) conducted between 2014 and 2017 in Burkina Faso and Mali. We compared K estimates using complete (weight-for-length z score, mid-upper arm circumference (MUAC), and edema) and partial (MUAC, edema) definitions of SAM and MAM. $K$ estimates for SAM were 9.4 and 5.7 in Burkina Faso and in Mali, respectively; K estimates for MAM were 4.7 in Burkina Faso and 5.1 in Mali. The MUAC and edema–based definition of AM did not lead to different $K$ estimates. Our results suggest that $K$ can be reliably estimated when only MUAC and edema-based data are available. Additional studies, however, are required to confirm this finding in different settings.
Stool frequency recording in severe acute malnutrition (‘StoolSAM’); an agreement study comparing maternal recall versus direct observation using diapers
