RT Journal Article
T1 Bayesian mixed effect models to account for environmental modulators of acute malnutrition treatment in children
A1 Sánchez Martínez, Luis Javier
A1 Faes, Christel
A1 Charle-Cuéllar, Pilar
A1 Samake, Salimata
A1 Samake, Mahamadou N’tji
A1 Bagayoko, Aliou
A1 Bunkembo, Magloire
A1 Gado, Abdoul Aziz
A1 Sanoussi, Atté
A1 Ousmane, Nassirou
A1 Lazoumar, Ramatoulaye Hamidou
A1 Hernández De La Fuente, Candelaria Lucía
A1 López Ejeda, Noemí
AB Acute child malnutrition is not only a global public health problem influenced not only by very diverse factors, including socioeconomic and dietary aspects, but also by seasonal and geographic factors. The present study is a secondary analysis that attempts to characterize which variables have influenced the Middle Upper-Arm Circumference (MUAC) upon admission and the Length of Stay (LOS) for treatment recovery. The sample of children analysed was 852. Initially, data cleaning and a reduction of the dimensionality of dietary diversity were carried out. A selection of the importance of the variables using the Watanabe Akaike Information Criteria (WAIC) was carried out prior to the adjustment of Bayesian mixed effects models, with the variables of travel time to health site and week of admission as random factors, on the MUAC and LOS variables. Clear differences were seen between both contexts, highlighting significant interactions of travel time in Niger while the seasonal effect stood out in Mali. The MUAC models identified a positive effect of age in both contexts, and in Niger, influences of diet diversity, comorbidities, breastfeeding and vaccination appeared. On the other hand, the LOS models highlighted the severity upon admission, and, in Niger, also factors related to the treatment protocol and the distance to the water source, while in Mali, the quality of water was more decisive. The present study shows the importance of considering acute child malnutrition from a multidimensional and complex approach, where diverse factors (biological, socioeconomic, ecological, etc.) can influence directly or as modulators of the disease and its treatment.
PB Springer
SN 1352-8505
YR 2024
FD 2024-11-11
LK https://hdl.handle.net/20.500.14352/125273
UL https://hdl.handle.net/20.500.14352/125273
LA eng
NO Sánchez-Martínez, L.J., Faes, C., Charle-Cuéllar, P. et al. Bayesian mixed effect models to account for environmental modulators of acute malnutrition treatment in children. Environ Ecol Stat 32, 1115–1141 (2025). https://doi.org/10.1007/s10651-025-00674-6
NO Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This research project was funded by Elrha's Research for Health in Humanitarian Crisis (R2HC) programme. R2HC aims to improve health outcomes for people affected by crises by strengthening the evidence base for public health interventions. The R2HC programme is funded by the UK Foreign, Commonwealth and Development Office (FCDO), Wellcome and the UK National Institute for Health Research (NIHR). LJ Sánchez-Martínez was granted a predoctoral fellowship from the Complutense University and Banco Santander.013/2020/CNERSAcknowledgements: The authors would like to express their gratitude to all medical staff and patients who participated in this study at Niger and Mali.
NO UK Foreign, Commonwealth and Development Office (FCDO)
NO Wellcome Trust  UK National Institute for Health Research (NIHR)
NO Universidad Complutense de Madrid
NO Banco de Santander
DS Docta Complutense
RD 19 ene 2026